Literature DB >> 35617253

Health care expenditures among long-term survivors of pediatric solid tumors: Results from the French Childhood Cancer Survivor Study (FCCSS) and the French network of cancer registries (FRANCIM).

Daniel Bejarano-Quisoboni1,2,3,4, Nathalie Pelletier-Fleury2,3, Rodrigue S Allodji1,3,4, Brigitte Lacour5,6, Pascale GrosClaude7, Hélène Pacquement8, François Doz8,9, Delphine Berchery10, Claire Pluchart11, Piere-Yves Bondiau12, Julie Nys1,4, Angela Jackson1,3,4, Charlotte Demoor-Goldschmidt1,13, Agnès Dumas14, Cécile Thomas-Teinturier1,15, Giao Vu-Bezin1,4, Dominique Valteau-Couanet16, Nadia Haddy1,3,4, Brice Fresneau1,3,16, Florent de Vathaire1,3,4.   

Abstract

BACKGROUND: Childhood cancer survivors (CCS) may require lifelong medical care due to late effects of cancer treatments. Little is known about of their healthcare utilization and expenditures at long-term especially in publicly funded health care system. We aim to estimate and describe the health care expenditures among long-term CCS in France.
METHODS: A total of 5319 five-year solid CCS diagnosed before the age of 21 between 1945 and 2000 in France were identified in the French Childhood Cancer Survivors Study cohort (FCCSS) and the French cancer registry. Information about health care expenditure was taken from the French national health data system between 2011 and 2016, and was described according to survivors' characteristics. Generalized linear models were used to determine associations between health care expenditures and survivors' characteristics.
RESULTS: Mean annual amount of healthcare expenditures was € 4,255. Expenditures on hospitalizations and pharmacy represents 60% of total expenditures. Mean annual of healthcare expenditures were higher at increasing age, among women survivors (€ 4,795 vs € 3,814 in men) and in central nervous system (CNS) tumor survivors (€ 7,116 vs € 3,366 in lymphoma and € 3,363 in other solid tumor survivors).
CONCLUSIONS: Childhood cancer survivorship is associated with a substantial economic burden in France. We found that female gender and CNS primary cancer were associated with increased healthcare expenditures.

Entities:  

Mesh：

Year:  2022        PMID： 35617253      PMCID： PMC9135272          DOI： 10.1371/journal.pone.0267317

Source DB:  PubMed          Journal:  PLoS One        ISSN： 1932-6203            Impact factor:   3.752


Introduction

Childhood cancer survivorship has improved considerably in the last few decades. Nowadays, more than 80% of pediatric cancer patients reach 5-year survival, leading to a growing number of long term survivors. In Europe, it is estimated that there are between 300,000 and 500,000 former pediatric cancer patients [1]. Nevertheless, most of this progress has been obtained using treatments that can damage healthy tissues. Consequently, childhood cancer survivors (CCS) carry a significant risk of cancer treatments related late effects [2]. Main late effects are secondary neoplasms, cardiac-vascular diseases, growth problems, mental health issues, infertility and organ dysfunction [3]. Therefore, long-term after-cancer care involves lifelong medical visits and tests to prevent and manage these potential life-threatening or disabling late effects [4]. This higher burden of morbidity and surveillance of late effects is likely associated with higher costs to the health care system [5]. Moreover, previous studies have shown that some CCS could have difficulties into educational attainment and are more likely to be unable to work or to miss work days due to health conditions [6-8]. Under those circumstances, a better understanding of the healthcare use and expenditure of CCS is important to evaluate long-term consequences of survivorship. In France, there are about 50,000 adults who had cancer in their childhood [9]. Healthcare system in France is mainly publicly funded and provides universal coverage to its citizens covering most medical expenses [10] especially for long-term conditions, however, no studies have estimated the global healthcare expenditures among CCS. The French Childhood Cancer Survivor Study (FCCSS) which includes CCS treated before 2001 provides an opportunity to detail the overall healthcare expenditures among very long-term cancer survivors. Nevertheless, FCCSS survivors were treated during their childhood in Centers for the fight against cancer (CLCC) which are specialized hospitals in cancer treatment in France. Therefore, we hypothesize that the FCCSS could include patients with more advanced and/or aggressive cancers, or they may have received more innovative treatments and consequently differ in terms of long-term outcomes and future health expenses from other CCS treated in other hospital settings. The aims of this paper was to quantify and describe the health care expenditures among very long-term CCS in France. Subsequently, we compared the level of expenditures between FCCSS survivors with those from other settings included in the French cancer registries existing during FCCSS recruitment period.

Material & methods

Study population

We used data from two sources, a multicenter cohort study (FCCSS) and the French Network of cancer registries (FRANCIM). The FCCSS is a retrospective cohort of 7,670 five-year CCS diagnosed for solid cancer or lymphoma (all malignancies except leukemia), before the age of 21 years between 1945 and 2000. Detailed information on the methods for data collection and validation has been already described [11, 12]. FRANCIM includes all the population-based registries of cancer in France. This network records all newly diagnosed and confirmed cancer cases since 1975 in diverse areas of France [13, 14]. The population covered by the FRANCIM’s database represents 22% of the French population [15]. Therefore, the FCCSS survivors who were included also in FRANCIM were considered as FCCSS patients. Leukemia survivors from FRANCIM were excluded for better comparability with the FCCSS which did not include leukemia. From both data bases, we selected all five-year solid CCS diagnosed before January 2001 who were alive in January 2011 and who were linked to the National Health Data System (Système National des Données de Santé) (SNDS). Since no social security number is collected in the study, patients are identified within the SNDS by probabilistic matching with the full involvement of different French healthcare-related organizations: Caisse nationale de l’assurance vieillesse des travailleurs salaries (CNAVTS) is the third party for social security number reconstruction and Caisse Nationale d’Assurance Maladie des Travailleurs Salaries (CNAMTS) is the trust third party for SNDS health data gathering based on a non-identifiable number derived from the retrieved social security number. The highly specific identification data that are provided to CNAMTS by the National Institute of Health and Medical Research (INSERM) are listed as below: family and first name, sex, date and place of birth and, unique arbitrary number. CNAMTS was in charge of both communication with CNAVTS and SNDS data extraction. The percentage of survivors linked to SNDS data after this procedure was 55.6% (n = 3786) for FCCSS and 71.9% (n = 2031) for FRANCIM survivors. In the present study, French national security number is not held by INSERM at any time. Survivors were followed throughout the SNDS until December 2016 or death. We excluded survivors who lived outside metropolitan France during follow-up due to the difference in the health insurance system, characteristics of the population and funding of care in French overseas territories [16]. The study was approved by the French Data Protection Authority (CNIL) (Authorization n°902287) and by the ethics committee of the INSERM. Patient informed consent was not required for this study because we obtained a specific act in law from the French “Conseil d’Etat”, the highest court in France (Order 2014–96 of 2014 February 3), that approved the cession of the SNDS data for all patients included in the FCCSS and FRANCIM.

Data sources

The SNDS is the health care claims dataset in France, which contains exhaustive individual data used for the billing and reimbursement data of the beneficiaries of the various national health insurance schemes which now covers more than 95% of the French population [17, 18]. The SNDS is mainly composed by the outpatient healthcare consumption database (Données de Consommation Inter-Régimes database, DCIR) and the private and public hospital database (Programme de Médicalisation des Systèmes d’Information, PMSI) which is divided in four categories: Medicine, surgery and obstetrics hospitalizations (MCO), home hospitalizations (HAD), after-care and rehabilitation (SSR) and psychiatry (PSY). Although MCO and HAD had cost information since 2006, the availability of billing records for PSY and SSR systems began in 2011, thus we established this year as starting date when data was available for all systems. Information in the SNDS includes some demographic characteristics (age, gender, place of residence); diagnosis of long-term conditions (affections de longue durée) defined as a disease in which the severity and/or the chronicity require a long-term costly treatment; as well as dates, nature and reimbursement of outpatient visits, dispensed medication, allied health professional visits, lab tests, medical devices, medical transports, paid sick leave and hospital admissions, including procedures performed within diagnosis‐related groups [18].

Primary measures

This study was carried out from the Assurance Maladie (AM) [French national health insurance] perspective (payer). Expenditures were estimated considering all the reimbursements made by the AM between January 2011 and December 2016 or date of death. Therefore, reimbursements from private health insurance, especial schemes or the final out-of-pocket were not included. Our primary outcome variables were the total sums of direct healthcare expenditure for every calendar year for each patient in both cohorts. Direct expenditure was also classified for every year into fourteen categories: General practitioner visits, other specialist visits, physiotherapy, nursing visits, other health professionals visits, pharmacy, medical device, laboratory test, technical medical procedures, transport, hospitalizations, disability benefits, sick leave and others. All expenditures were expressed in real terms using the consumer price index with a 2015 base year provided by the National Institute of Statistics and Economic Studies (INSEE).

Covariates

Other covariates included age, sex, year of diagnosis, age at diagnosis, type of primary cancer (kidney tumor, neuroblastoma, lymphoma, soft tissue sarcoma, bone sarcoma, central nervous system tumor, gonadal tumor, thyroid tumor, retinoblastoma and others), French deprivation index in 2009 which is an area-based multidimensional index that measures socioeconomic differences [19] and where higher scores implies a higher "deprivation" (categorized into quintiles), and death (alive or death at December 2016).

Statistical analysis

Patient’s characteristics were described along with the estimation of annual mean expenditure over 2011–2016 period. Categorical variables were expressed as numbers and percentages, and continuous variables as mean ± SD. Direct total expenditures were described by categories and also according to primary cancer. Given the population studied, the frequency of persons having no healthcare expenses during the 6 years follow-up period was less than 4% of the total patients within each cohort group, therefore a 2-stage model was not required. Instead, we used a repeated measures generalized linear model (GLM) with a gamma distribution and a log link to estimate per-person annual medical expenditures for all patients accounting the skewness in the distribution. We added 1€ to all expenditures to allow inclusion of individuals with no expenses [20] and used age at diagnosis as categorical variable in the models due to the strong correlation with age at follow-up and year of diagnosis. Neuroblastoma was chosen as the referent for type of primary cancer variable since was one of the larger group of cancer of same histology. We compared the output of the model adjusted by all covariates (Model I), with models excluding variable of death (Model II) and patients who died (Model III). Finally, we performed several analysis by considering separately each type of expenditure and each type of cancer along with different interactions between cohort (FCCSS or French cancer registries) and type of cancer. Statistical significance was determined using p<0.05. All analyses were performed using SAS 9.4 software (SAS Institute, Cary, NC, USA).

Results

Survivors’ characteristics and total health care expenditure

A total of 5,319 CCS were included in the study, among which 67.5% belong to the FCCSS (Table 1). Almost half of the patients were women and were diagnosed after 1990 (44.9% and 46.6% respectively). More than 50% of the patients were over 30 years old at the beginning of follow-up. The most common primary cancer was lymphoma (20.1%) followed by central nervous system (CNS) tumor (14.2%). Between 2011 and 2016, around 3% of the total patients had died. Details of patient characteristics by cohort are shown in the S1 and S2 Tables.
Table 1

Survivors characteristics and health care expenditures.

 N° PatientsPYAnnual Health care expenditures
 (%)Mean (SD)Median (IQR)
Total531931533.64255 (18790)494 (105–2151)
Sex
    Man2929 (55.1)17351.93814 (19289)338 (64–1554)
    Women2390 (44.9)14181.74795 (18147)721 (198–3290)
Year of childhood cancer diagnosis
    <1980988 (18.6)5760.36970 (28210)995 (242–4552)
    1980–19891852 (34.8)10974.54731 (20024)607 (149–2749)
    > = 19902479 (46.6)14798.82841 (11813)326 (52–1334)
Age at childhood cancer
    0–1937 (17.6)5575.02905 (9828)257 (15–1337)
    2–41034 (19.4)6140.24926 (26253)413 (69–2003)
    5–91088 (20.5)6433.34420 (14300)552 (126–2743)
    10–141130 (21.2)6685.25072 (24480)640 (170–2686)
    ≥151130 (21.2)6699.83790 (12352)600 (179–2135)
Age at January 2011 (Start date)
    <20550 (10.3)3291.91475 (8143)0 (0–309)
    20–301979 (37.2)11812.83561 (13189)443 (113–1891)
    31–401878 (35.3)11142.64303 (20597)592 (157–2312)
    41–50753 (14.2)4355.47676 (29734)1072 (265–5056)
    > = 51159 (3)930.96233 (14164)1378 (398–5272)
French geographical deprivation index**
    1 Quintile1063 (20)6312.94569 (24995)459 (92–1952)
    2 Quintile1061 (19.9)6293.33688 (11473)507 (118–2020)
    3 Quintile1066 (20)6322.34034 (16209)471 (103–1920)
    4 Quintile1064 (20)6320.54699 (23783)507 (97–2374)
    5 Quintile1065 (20)6284.64283 (13374)539 (119–2529)
First primary cancer type
    Kidney tumors668 (12.6)3942.05021 (30330)383 (78–1776)
    Neuroblastoma574 (10.8)3434.22952 (12224)285 (37–1301)
    Lymphoma1071 (20.1)6350.73366 (10662)442 (106–1770)
    Soft tissue sarcomas523 (9.8)3117.34007 (14074)471 (108–2219)
    Bone sarcomas445 (8.4)2636.75207 (14193)827 (188–4303)
    Central nervous system tumor756 (14.2)4427.77116 (29617)1130 (256–4925)
    Gonadal tumor389 (7.3)2322.33575 (15215)392 (93–1401)
    Thyroid tumor109 (2)650.73202 (7882)785 (348–2210)
    Retinoblastoma305 (5.7)1815.52852 (9698)235 (0–1161)
    Other solid cancer479 (9)2836.53363 (12231)495 (143–1797)
Cohort
    FCCSS3589 (67.5)21247.64556 (18830)507 (97–2297)
    French cancer registry1730 (32.5)10286.03633 (18692)476 (122–1890)
Status at December 2016 (Ending date)
    Alive5152 (96.9)30912.03770 (17677)473 (101–2003)
    Death167 (3.1)621.625611 (40950)10208 (1437–34703)

PY: Person-years of follow-up, SD: Standard deviation, IQR: Inter Quartile Range.

**: Ecological Index measuring the deprivation, and based on the median household income, the percentage high school graduates in the population aged 15 years and older, the percentage blue-collar workers in the active population, and the unemployment rate [19].

PY: Person-years of follow-up, SD: Standard deviation, IQR: Inter Quartile Range. **: Ecological Index measuring the deprivation, and based on the median household income, the percentage high school graduates in the population aged 15 years and older, the percentage blue-collar workers in the active population, and the unemployment rate [19]. Total direct healthcare expenditure for the 5,319 patients between 2011 and 2016 were € 134,523,643. Annual mean of health care expenditures of survivors was € 4,255. However, this variable was positive skewed due to a few very high values among survivors. In detail, 50% of patients had an annual mean of healthcare expenditures lower than € 1,000 and almost 10% was above € 10,000 (S1 Fig). On average, annual health care expenditures was higher in women than men (€ 4,795 and € 3,814), survivors diagnosed before 1980 (€ 6,970) who likely correspond with survivors between 41–50 years old (€ 7,676), among diagnosed with CNS tumor (€ 7,116), and in FCCSS (€ 4,556 vs € 3,663 in FRANCIM) (Table 1). It is noteworthy that the 167 survivors who died between 2011 and 2016, had an annual mean of expenditures of € 25,611 and accounted for 13.4% of the total expenditures.

Healthcare utilization

Health care expenditures by items are reported in Table 2. The leading expenditure item was hospitalizations which represents 45% of total expenses and were experienced by 65% of survivors during the study period. The number of hospitalizations was higher in women than in men (73% vs 59%) (S3 Table). The annual mean for hospitalization expenses was € 1,919. Pharmacy was also an important expenditure item representing 16% of total healthcare expenditure with an annual mean of € 676 per patient (€ 719 in men vs 622 in women).
Table 2

Health care expenditures by items.

 N° Patients (%)N° ClaimsTotal Expenditures in Millions € (%)Annual mean Expenditure Per-Patient in €* (SD)
General practitioner visits5,055 (95)144,1073.1 (2.3)97 (133)
Other specialists visits4,935 (92.8)161,9985.4 (4)170 (439)
Physiotherapy visits2,195 (41.3)123,8282.1 (1.6)67 (319)
Nursing visits3,519 (66.2)118,5481.7 (1.3)55 (650)
Other health professionals visits †597 (11.2)12,5480.4 (0.3)12 (135)
Pharmacy5,046 (94.9)502,87221.4 (15.9)676 (9,736)
Medical device4,223 (79.4)52,4798.2 (6.1)260 (1,800)
Laboratory test4,597 (86.4)101,2462.5 (1.9)80 (302)
Technical medical procedures ‡4,700 (88.4)48,5832.6 (1.9)83 (287)
Transport1,743 (32.8)24,6044.4 (3.3)140 (979)
Hospitalizations3,450 (64.9)35,00160.7 (45.1)1,919 (13,730)
Disability Benefits §345 (6.5)13,8637.9 (5.9)251 (1,538)
Sick Leave2,731 (51.3)41,72213.0 (9.6)410 (1,623)
Others571 (10.7)3,4421.2 (0.9)37 (1,039)
Total5,3191,384,841134.54,255 (18,790)

* Annual mean expenditure per-patient in € were calculated for the entire population (= 5,319). † Other medical professional visits included expenditures related to visits to podiatrist, optometrists, speech therapist, and others ‡ Technical medical procedures includes expenditures mainly related to medical imaging techniques. § Disability benefits includes all welfare payments or pensions made by the French Government to assistance people with disabilities.

* Annual mean expenditure per-patient in € were calculated for the entire population (= 5,319). † Other medical professional visits included expenditures related to visits to podiatrist, optometrists, speech therapist, and others ‡ Technical medical procedures includes expenditures mainly related to medical imaging techniques. § Disability benefits includes all welfare payments or pensions made by the French Government to assistance people with disabilities. Around half of survivors received sick leave during the 6-year follow-up and their annual mean per patient was € 410 but notably was almost the double for women than for men (€ 557 vs 289) (S3 Table). On the contrary, only 6.5% of patients had expenditures related to disability benefits but their cost reached almost € 8 million which is more than 5% of the total expenses. The distribution of health care expenditure by items was quite similar in both cohorts (S4 Table).

Health care expenditure by type of primary cancer

Details on expenditures by each type of primary cancer are shown in Table 3. Survivors from CNS tumors had the highest annual mean of hospitalizations expenses (€4,142), while kidney tumor survivors had the highest annual mean of pharmacy (€ 1,578) compared with the other types of cancer. Disability benefits annual mean were higher among bone sarcoma survivors (€ 479) while sick leave where major for thyroid tumor survivors (€ 708).
Table 3

Annual mean and percentage* (%) of healthcare expenditures items by type of primary cancer.

 Kidney tumors (n = 668)Neuroblastoma (n = 574)Lymphoma (n = 1071)Soft tissue sarcomas (n = 523)Bone sarcomas (n = 445)Central nervous system tumor (n = 756)Gonadal tumor (n = 389)Thyroid tumor (n = 109)Retinoblastoma (n = 305)Other solid cancer (n = 479)
General practitioner visits84 (1.7)70 (2.4)96 (2.8)94 (2.4)116 (2.2)130 (1.8)81 (2.3)128 (4)72 (2.5)102 (3)
Other specialist visits172 (3.4)134 (4.5)185 (5.5)162 (4.1)179 (3.4)181 (2.5)160 (4.5)250 (7.8)126 (4.4)182 (5.4)
Physiotherapy37 (0.7)35 (1.2)49 (1.5)55 (1.4)90 (1.7)182 (2.6)37 (1)40 (1.2)21 (0.7)59 (1.8)
Nursing visits39 (0.8)57 (1.9)35 (1)55 (1.4)28 (0.5)144 (2)29 (0.8)22 (0.7)25 (0.9)56 (1.7)
Other health professionals visits5 (0.1)8 (0.3)7 (0.2)9 (0.2)4 (0.1)39 (0.5)4 (0.1)15 (0.5)1 (0)16 (0.5)
Pharmacy1578 (31.4)350 (11.8)498 (14.8)469 (11.7)564 (10.8)864 (12.1)777 (21.7)944 (29.5)220 (7.7)397 (11.8)
Medical device288 (5.7)201 (6.8)131 (3.9)275 (6.9)956 (18.4)295 (4.2)80 (2.2)56 (1.7)124 (4.3)138 (4.1)
Laboratory test99 (2)63 (2.1)85 (2.5)67 (1.7)80 (1.5)87 (1.2)74 (2.1)130 (4)49 (1.7)81 (2.4)
Technical Medical Procedures74 (1.5)54 (1.8)81 (2.4)90 (2.3)104 (2)93 (1.3)101 (2.8)110 (3.4)57 (2)81 (2.4)
Transport159 (3.2)107 (3.6)88 (2.6)107 (2.7)183 (3.5)286 (4)94 (2.6)35 (1.1)160 (5.6)85 (2.5)
Hospitalizations1827 (36.4)1401 (47.5)1345 (40)1831 (45.7)1863 (35.8)4142 (58.2)1500 (42)658 (20.6)1731 (60.7)1384 (41.2)
Disability Benefits245 (4.9)152 (5.1)276 (8.2)287 (7.2)479 (9.2)303 (4.3)205 (5.7)91 (2.9)69 (2.4)176 (5.2)
Sick Leave380 (7.6)309 (10.5)460 (13.7)482 (12)532 (10.2)266 (3.7)412 (11.5)708 (22.1)182 (6.4)565 (16.8)
Others34 (0.7)12 (0.4)30 (0.9)23 (0.6)30 (0.6)103 (1.4)19 (0.5)15 (0.5)15 (0.5)39 (1.2)
Total5 021 €2 952 €3 366 €4 007 €5 207 €7 116 €3 575 €3 202 €2 852 €363 €

* Percentage (%) of each expenditure items were calculated for each primary cancer population.

* Percentage (%) of each expenditure items were calculated for each primary cancer population.

Multivariate analysis of survivor’s characteristics impact on healthcare expenditures

Table 4 shows the estimations of the GLM model using gamma distributions after adjusting by patients’ characteristics. Total healthcare expenditures were higher at increasing age (Beta: 0.04, p = < .0001), in women (Beta: 0.30, p = < .0001), in patients treated for CNS tumor (Beta: 0.70, as compared to neuroblastoma, p = < .0001), in patients treated between aged 2 and 4 (Beta: 0.36, as compared to age 0–1, p = 0.05) and among survivors who died during 2011 and 2016 (Beta: 1.85, p = < .0001). Annual healthcare expenditures of survivors from FCCSS were not significantly higher than survivors’ expenditures from FRANCIM (Beta: 0.12, p = 0.23). These results did not vary by excluding variable “death” from the model or excluding deceased survivors from the study population (Model II and III, respectively).
Table 4

Multivariate analysis*.

Total Patients (n = 5,319)Patients Alive (n = 5,152)
 Model IModel IIModel III
 BetaPr > |Z|BetaPr > |Z|BetaPr > |Z|
Intercept11.540.691.260.9621.670.45
Women0.30< .00010.27< .00010.31< .0001
Age0.04< .00010.06< .00010.04< .0001
Year of Diagnosis0.000.850.000.86-0.010.59
Age at first cancer (Ref = 0–1)
    2–40.360.050.330.060.370.05
    5–90.080.640.070.690.100.56
    10–140.160.500.080.720.200.38
    ≥15-0.030.92-0.160.570.040.90
French Index Deprivation0.020.470.040.270.030.40
First primary cancer type (Ref = Neuroblastoma)
    Kidney tumor0.190.460.320.170.200.46
    Lymphoma-0.120.540.030.86-0.130.50
    Soft tissue sarcoma-0.030.870.070.71-0.040.83
    Bone sarcoma0.300.140.410.040.300.14
    Central nervous system tumor0.70< .00010.86< .00010.72< .0001
    Gonadal tumor0.080.770.080.740.090.74
    Thyroid tumor0.010.980.010.980.020.95
    Retinoblastoma0.050.790.320.130.020.92
    Other solid cancer-0.050.810.110.59-0.050.80
FCCSS Survivors0.120.230.140.160.120.22
Death1.85< .0001....

* GLM model using gamma distributions. Model I were adjusted using all variables. Model II excluded “death” variable. Model III excluded dead patients.

* GLM model using gamma distributions. Model I were adjusted using all variables. Model II excluded “death” variable. Model III excluded dead patients. Fig 1 shows the adjusted estimates for the annual mean of healthcare expenditures from the gamma model by type of primary cancer. Survivors with neuroblastoma, lymphoma, soft tissue sarcoma, gonadal, thyroid tumor and other solid tumors had similar annual mean of health care expenditures between 3,000 and 3,500 euros whereas, survivors with kidney tumor, bone sarcoma and retinoblastoma had a similar mean of expenditures around 4,000 and 4,500 euros per year.
Fig 1

Adjusted* annual health care expenditures by type of primary cancer.

* Adjusted by age, sex, year of diagnosis, age at diagnosis, French index deprivation, cohort and type of primary cancer. Type of primary cancer: Kidney tumor, neuroblastoma, lymphoma, soft tissue sarcoma, bone sarcoma, central nervous system tumor (CNS), gonadal tumor, thyroid tumor, retinoblastoma and other solid cancer.

Adjusted* annual health care expenditures by type of primary cancer.

* Adjusted by age, sex, year of diagnosis, age at diagnosis, French index deprivation, cohort and type of primary cancer. Type of primary cancer: Kidney tumor, neuroblastoma, lymphoma, soft tissue sarcoma, bone sarcoma, central nervous system tumor (CNS), gonadal tumor, thyroid tumor, retinoblastoma and other solid cancer. Finally, we investigated each item of the healthcare expenditure separately and showed that women had significantly higher adjusted expenditures than men, for all items, excepted for disability benefits, other health professionals visits, pharmacy, and medical device (S5 Table). Men survivors from FCCSS had higher adjusted expenses than the ones from FRANCIM, this difference was not observed in women (interaction p = <0.001) (S2 Fig). Lastly, no global interaction was shown between the type of primary cancer and the origin of patients, FCCSS or FRANCIM (S3 Fig).

Discussion

To our knowledge, this is the first detailed study of the economic burden of childhood cancer survivors in France. We found that the annual mean of healthcare expenditures among CCS were € 4,255, which are composed mainly by expenditures on hospitalizations and pharmacy. Additionally, we showed that women had higher expenditures than men, and that CNS tumor survivors had the highest expenditures. Although, FCCSS survivors had higher expenditures than those from FRANCIM, this difference was no longer significant when adjusting on childhood cancer type and on demographics. CCS have a high rate of illness due to chronic health conditions [21] and require significantly more healthcare resources than the general population [5]. Previous studies have shown that their hospitalization rates are almost twofold increase and their stay was 35% longer than for patients without a cancer history [22]. Consequently, their medical needs translate into substantial healthcare expenditures. In United States, CCS were more likely to have out-of-pocket medical costs [23], and up to 33% of them were unable to see a doctor or go to the hospital due to financial issues [24]. Annual medical expenditures in adolescent or young adult cancer survivors (age 15–35) has been estimated to $7,417 [25], while annual productivity loss among adult survivors of childhood (<14 years at diagnosis) cancer was estimated to $8,169 [8]. In Norway, survivors of cancer at young age have by a four-to fivefold increased risk of not being employed and receive governmental financial assistance than general population [26]. However, it is important to keep in mind that since the nineties, the rate of iatrogenic events decreases because of the reduction in the use of radiation therapy, and more recently, it could be anticipate that this risk will continue to decrease, in particular because of the emergency of proton-therapy [27]. We also highlighted that a few number of CCS especially survivors who die during the follow up period, were the main expenditure drivers. Most of these deaths have been found related to childhood cancer recurrence during the first two decades and to treatment-related sequelae including cardiovascular diseases and second malignant neoplasms, afterward [28]. The mean expenditures during the last year of life in some types of cancer have been estimated up to 43,000 euros in France [29, 30] which correlates well with our results. Our findings showing that women survivors have a higher annual mean both in total healthcare expenditures and in several specific expenditures items are in agreement with several studies that have shown that hospitalizations occurred more often among females survivors [31, 32], mostly due to endocrine, metabolic and nutritional disorders and subsequent neoplasms [33]. Additionally all the expenditures associated with pregnancies and perinatal conditions were included in the health expenditures in our analysis. Moreover, women survivors have higher rates of miscarriage or preterm birth than the general population, including risks to both the mother and the fetus [34], which could at least partly explain the difference in the healthcare utilization compared with men survivors. As expected, expenditures were also higher in CNS tumor survivors. A previous study showed that the cumulative burden of chronic health conditions at age 50 was higher in CCS with CNS tumor than in CCS with any other cancer [35]. This, together with the evidence that survivors from CNS tumor have at least one disability condition [36], were less likely to progress in educational attainment [37] and to have a higher risk of unemployment and reduced incomes compared with the cancer-free population [26, 38], explained their excess of healthcare expenditures. Additionally, progressive disease or relapses more than 5 years after diagnosis of a brain tumor in children is common, particularly, in slowly evolving low grade tumors [39]. Despite the fact that FCCSS survivors were treated in specialized centers to treat cancer, and thus could have been more adverse cases or received a more intense treatment, no significant difference in expenses were found at long term when adjusting on demographical factors and type of childhood cancer to others CCS in France. Although, survivors from FCCSS were younger at time of diagnosis and were recruited in early years than survivors from French cancer registries, they weren’t particularly older during follow-up period. An advantage of our study is to have worked on a large sample of long term survivors. Also, we used a national administrative database which allowed accounting for comprehensive health care expenditures during six years using two sources of long-term CCS in France. Another strength is the inclusion period starting in 1945, which allows us to study variations in cost across the age spectrum. However, our study is subject to some limitations. First of all, data for a cancer-free control group were not available, which limited our results to the CCS population. Secondly, FRANCIM is a network of population-based registries which does not have national coverage. Thirdly, we were unable to address the association between cancer treatments received by survivors and health expenditures, due to the lack of therapeutic information in survivors from FRANCIM. All in all, our findings provide a first estimation on annual expenditures and the economic burden of CCS in France by type of childhood cancer, and demographical characteristics of survivors. Additionally, transferability to other contexts may be limited to the France territory.

Conclusion

We have estimated and described the magnitude of health expenditures related to consequences in adulthood of having had cancer treated in childhood. These high expenditures in relation to the age of survivors are related to the more frequent multimorbidity than in the general population. These results lead us to recommend that special attention be paid to this population, particularly in terms of prevention of complications and early medical follow-up. Future research should focus on addressing in deep the relationship between cancer treatment and future healthcare expenditures to establish long-term cost-effectiveness of childhood cancer treatment.

Participating French administrative areas in FRANCIM.

(DOCX) Click here for additional data file.

Survivor’s characteristics by cohort.

(DOCX) Click here for additional data file.

Health care expenditures by sex.

(DOCX) Click here for additional data file.

Health care expenditures by cohort.

(DOCX) Click here for additional data file.

Multivariate analysis for each type of expenditure.

(DOCX) Click here for additional data file.

Multivariate analysis for total health care expenditure by each type of cancer.

(DOCX) Click here for additional data file.

Histogram of the survivors mean of healthcare expenditures.

(TIF) Click here for additional data file.

Adjusted annual health care expenditures by sex and cohort.

(TIF) Click here for additional data file.

Adjusted annual health care expenditures by type of primary cancer and cohort.

(TIF) Click here for additional data file. 13 Jan 2022
PONE-D-21-17399
Health care expenditures among long-term childhood cancer survivors in France PLOS ONE Dear Dr. de Vathaire, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. The manuscript has been evaluated by two reviewers, and their comments are available below. The reviewers have raised a number of major concerns. They feel that the title of the article should clarify the sub-population of childhood cancer survivors under investigation, and the Introduction and the Discussion should clarify the exclusion of non-cancer comparison group. They request improvements to the reporting of methodological aspects of the study, for example, regarding the data source. The reviewers also note concerns about the language and request copy-editing. Could you please carefully revise the manuscript to address all comments raised? Please submit your revised manuscript by Feb 26 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript:
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Once you have amended this/these statement(s) in the Methods section of the manuscript, please add the same text to the “Ethics Statement” field of the submission form (via “Edit Submission”). For additional information about PLOS ONE ethical requirements for human subjects research, please refer to http://journals.plos.org/plosone/s/submission-guidelines#loc-human-subjects-research. 3. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match. When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section. 4. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. 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The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes ********** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ********** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. 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(Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The authors present an analysis that examines healthcare expenditure from 2011-2016 among childhood cancer survivors in France diagnosed between 1945 and 2000. Financial toxicity and cost of health care expenditure among childhood cancer survivors is very topical. The manuscript is well written and generally easy to follow. There are some grammatical issues that will need to be addressed during copy-editing. I have provided some comments for the authors to consider which are provided in no particular order. - The title of the article needs to indicate the sub-population of childhood cancer survivors under investigation. - The second sentence of the introduction describes an observed survival proportion, but the authors refer to this as a rate. Please remove the word ‘rates’ from this sentence. - In the third paragraph of the introduction, the authors describe the data source (FCCSS). I think this information belongs in the methods section where the data source should be described. At the end of this paragraph the authors hypothesize about a potential bias associated with the FCCSS. I wonder if there are any references that could be provided to highlight this? I also feel the authors need to consider this potential bias in the limitations section more fully specifically with regard to how to interpret the results presented in this analysis. - In the study population section, the authors indicate that the rates of linkage to the SNDS is 55.6% and 71.9% for each of the two data sources. Given this differential linkage and reasonably low rates of linkage there is opportunity for bias. The authors need to spend a little more time examining the factors that drive the variability in linkage. I would suggest a simple logistic regression analysis where the outcome is linked and various factors from table 1 can be included. This analysis may need to be stratified by data source to determine if the factors affecting linkage are different. The full results of this analysis need not be included in the manuscript, but can form the basis for a fulsome discussion about the potential bias, how it might be operating and the potential impact on the analysis presented. - It took me some time to consider the inclusion of the diagnoses in the early years (they start in 1945) given the observation window for the outcome only starts in 2011, but I think this approach is strong as it produces estimates across the age spectrum. - In the Primary Measures section, the authors indicate that the expenditures are expressed in real terms using the CPI. The authors need to be explicit in terms of the anchor year for the adjustment and provide a reference to the CPI data that was used for the adjustment. - Given the longitudinal nature of the outcome ascertainment, I think it would strengthen the paper to provide the person-years of follow-up in all of the tables. - Given what appears to be skewed nature of the expenditures, it might be more appropriate to provide the median and IQR or both the mean and SD and median and IQR. - There are two factors that likely drive 2 of the main results. The first is the higher costs among female survivors and the second is how death is related to higher costs. Neither of these are particularly surprising given births among female survivors are known to considerably contribute to health care costs. Is it possible for these costs to be removed for a sensitivity analysis so this could be examined? Further, could costs in the last period of life among those that die, say 6 or 8 weeks, be excluded so as to assess the timing of these costs relative to death? - In table 2 I struggle to make sense of the data presented. For example, consider paramedic, the annual mean expenditure per patient is presented as 12 so over the 6 year period of outcome assessment it would be 72. If I multiply this by the number of patients, 597, the total is 42,984 which is very different (by a factor of 10) than the 400,000 reported in the table. Why is this? Am I just miss-interpreting the table? - It would be good to include column percentages in table 3 so a reader could compare across groups. - Please include more explicit column headings or notes to describe in the table. It is difficult to understand the table in the absence of reading the manuscript. Reviewer #2: Thank you for the opportunity to review this manuscript. This is a population-based study of financial expenditures in registry-defined cohorts of childhood cancer survivors in France. The authors have documented the mean annual health system costs (i.e., excluding out of pocket expenses, etc.) from 2011-2016. The highest expenses were incurred for survivors of CNS tumors, survivors who were women and older during the study period. The data submitted are complete, statistical analyses correct, conclusions appropriate to results, and the paper is generally well-written. Please consider the following questions and comments, which are offered in hopes of strengthening this contribution: 1. Would the authors please provide an explanation in the Introduction and/or Discussion why they did not include a non-cancer comparison group matched for age, sex, and age at diagnosis? This would provide some perspective for these results, which are limited to the childhood cancer population. Also, this would help elucidate what role "normal" health care costs played, such as pregnancy in female survivors. 1a. The analysis does include the two oncology cohorts, one from the FCCSS and the other from FRANCIM. A more complete explanation of how these two sources complement each other in interpreting the data would enhance the conclusions (i.e., what were authors hoping to discover by comparing these two cohorts?). 2. Would the authors please explain why this sample was limited to solid tumors and excluded leukemias. 3. For the expenditures listed in Table 2, it would be helpful to define these terms/categories, as some are not self-evident. For example, what are "sick payments"-? Presumably these terms are defined within the French system but the terms may be ambiguous for other national systems. 4. Page 14, last paragraph, next to last line: a typographical error ("where" and should be "were"). 5. For the regression analysis on tumor type, can the authors please explain in the manuscript why neuroblastoma was chosen as the referent? 6. Page 19, second paragraph, the sentence beginning, "Studies from the United States..." is difficult to understand. Are there some words missing? It is informative, but also rather long and hard to follow. Consider clarifying the language and also splitting it up into at least 2 smaller sentences. 7. In the Introduction, the authors suggest the analysis would address potential differences between patients cared for in the private vs. public health systems. Was this reported in the Results? 8. Reference 27 does not have the year of publication. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. 25 Feb 2022 Dear Editor-in-chief, We are grateful to the editors and reviewers for their time and constructive comments on our manuscript. We have implemented their suggestions and answered their concerns which, we believe, allowed improving the manuscript. Changes in the initial version of the manuscript can be retrieved in the tracked change version. Below, we provide a point-by-point response explaining how we have addressed each of the editors or reviewers’ comments. We look forward to receiving your further evaluation of our manuscript. Sincerely, Florent de Vathaire, PhD Head of the Radiation Epidemiology Group Unit 1018 INSERM – CESP Institut Gustave Roussy 39, rue Camille Desmoulins 94805 Villejuif, France Tel: +33 1 42 11 54 57 Fax: +33 1 42 11 53 15 Email: florent.devathaire@gustaveroussy.fr Web: https://www.gustaveroussy.fr/ - https://cesp.inserm.fr/fr All page and line numbering below refers to the re-submitted clean copy, word document, which has been line numbered, before re-submission. Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf Our response: We thank the editor for your review. We have made several changes in order to fully meet PLOS ONE's style requirements. 2. Please provide additional details regarding participant consent. In the ethics statement in the Methods and online submission information, please ensure that you have specified (1) whether consent was informed and (2) what type you obtained (for instance, written or verbal, and if verbal, how it was documented and witnessed). If your study included minors, state whether you obtained consent from parents or guardians. If the need for consent was waived by the ethics committee, please include this information. If you are reporting a retrospective study of medical records or archived samples, please ensure that you have discussed whether all data were fully anonymized before you accessed them and/or whether the IRB or ethics committee waived the requirement for informed consent. If patients provided informed written consent to have data from their medical records used in research, please include this information. Once you have amended this/these statement(s) in the Methods section of the manuscript, please add the same text to the “Ethics Statement” field of the submission form (via “Edit Submission”). For additional information about PLOS ONE ethical requirements for human subjects research, please refer to http://journals.plos.org/plosone/s/submission-guidelines#loc-human-subjects-research. Our response: We have added more details regarding participant consent. Lines 133-137 “The study was approved by the French Data Protection Authority (CNIL) (Authorization n°902287) and by the ethics committee of the INSERM. Patient informed consent was not required for this study because we obtained a specific act in law from the French “Conseil d’Etat”, the highest court in France (Order 2014-96 of 2014 February 3), that approved the cession of the SNDS data for all patients included in the FCCSS and FRANCIM.” 3. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match. When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section. Our response: We have added more details regarding grant information of DBQ. However, for the other of grants or funding that we received we don’t have a grants numbers because the funders didn’t provide. DBQ received a doctoral grant from the Paris-Saclay University (N° contract 9R_2019_PSU000101141_Upsud). This work was funded by the Ligue Nationale Contre le Cancer (Grant N°RAB20035LLA). The FCCSS cohort was funded by the French Society of Cancer in Children and adolescents (SFCE), the Gustave Roussy Fondation, the Foundation ARC (POPHarC program) and The French National Research Agency (ANR, HOPE-EPI project). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. 4. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtxQ Our response: We have linked the ORCID account for the corresponding author, Florent de Vathaire (0000-0002-8374-9281). 5. One of the noted authors is a group or consortium FRANCIM-Group. In addition to naming the author group, please list the individual authors and affiliations within this group in the acknowledgments section of your manuscript. Please also indicate clearly a lead author for this group along with a contact email address. Our response: We added individual authors and affiliations of FRANCIM-Group in the acknowledgments section. The Lead author for this group is Florence Molinié (florence.molinie@chu-nantes.fr). Lines 378-389 “The authors thank the staff of each member of the FRANCIM network who participated in the collection of data; Claire Schvartz (Registre des Cancers Thyroidiens de la Marne et des Ardennes), Michel Velten (Registre des Cancers du Bas-Rhin), Anne-Valérie Guizard (Registre Général des Tumeurs du Calvados), Guy Launoy (Registre des tumeurs digestives du Calvados), Anne-Marie Bouvier (Registre Bourguignon des cancers Digestifs), Anne-Sophie Woronoff (Registre des tumeurs du Doubs), Karima Hammas (Registre des tumeurs du Haut-Rhin), Brigitte Trétarre (Registre des Tumeurs de l'Hérault), Marc Colonna (Registre du Cancers de l'Isère), Brigitte Lacour (Registre National des Tumeurs Solides de l'Enfant), Simona Bara (Registre des Cancers de la Manche), Clarisse Joachim (Registre de la Martinique), Bénédicte Lapôtre-Ledoux (Registre de la Somme), Pascale Grosclaude (Registre des Cancers du Tarn), and Florence Molinié (Registre de la Loire-Atlantique et Vendée)”. Reviewers' Comments to Author: Reviewer #1: The authors present an analysis that examines healthcare expenditure from 2011-2016 among childhood cancer survivors in France diagnosed between 1945 and 2000. Financial toxicity and cost of health care expenditure among childhood cancer survivors is very topical. The manuscript is well written and generally easy to follow. There are some grammatical issues that will need to be addressed during copy-editing. I have provided some comments for the authors to consider which are provided in no particular order. Our response: Thank you very much for your review. 1. The title of the article needs to indicate the sub-population of childhood cancer survivors under investigation. Our response: Taking up your suggestion, we have changed the title of the article to: “Health care expenditures among long-term solid childhood cancer survivors in France: Results from the French Childhood Cancer Survivor Study (FCCSS) and the French network of cancer registries (FRANCIM)”. 2. The second sentence of the introduction describes an observed survival proportion, but the authors refer to this as a rate. Please remove the word ‘rates’ from this sentence. Our response: The word “rate” has been removed (Line 69). 3. In the third paragraph of the introduction, the authors describe the data source (FCCSS). I think this information belongs in the methods section where the data source should be described. At the end of this paragraph the authors hypothesize about a potential bias associated with the FCCSS. I wonder if there are any references that could be provided to highlight this?. I also feel the authors need to consider this potential bias in the limitations section more fully specifically with regard to how to interpret the results presented in this analysis. Our response: Thank you very much for this comment. Indeed as said by the reviewer, we have hypothesized about the potential bias associated with the FCCSS because these patients were treated in Centers for the fight against cancer in France (French acronym: CLCC). These centers are dedicated to cancer treatment so we believe that they treat the most serious cancer patients or can provide a different kind of health care especially in pediatric patients (like survivors of the FCCSS) which would impact long-term patient outcomes and therefore be reflected in future costs. Our hypothesis then was that the FCCSS survivors would be patients with higher health care costs than other childhood cancer survivors treated in other facilities, because either they were more severe cases or they could have received more intense treatment that would leave more serious long-term late effects. However, until now we do not have any reference that could highlight this hypothesis, and one of the aim of this study was to investigate this issue. It is why we provide some details about the data source of the FCCSS in the introduction. We have made adjustments in the introduction to clarify this idea. Lines 87-95 “The French Childhood Cancer Survivor Study (FCCSS) which includes CCS treated before 2001 provides an opportunity to detail the overall healthcare expenditures among very long-term cancer survivors. Nevertheless, FCCSS survivors were treated during their childhood in Centers for the fight against cancer (CLCC) which are specialized hospitals in cancer treatment in France. Therefore, we hypothesize that the FCCSS could include patients with more advanced and/or aggressive cancers, or they may have received more innovative treatments and consequently differ in terms of long-term outcomes and future health expenses from other CCS treated in other hospital settings. 4. In the study population section, the authors indicate that the rates of linkage to the SNDS is 55.6% and 71.9% for each of the two data sources. Given this differential linkage and reasonably low rates of linkage there is opportunity for bias. The authors need to spend a little more time examining the factors that drive the variability in linkage. I would suggest a simple logistic regression analysis where the outcome is linked and various factors from table 1 can be included. This analysis may need to be stratified by data source to determine if the factors affecting linkage are different. The full results of this analysis need not be included in the manuscript, but can form the basis for a fulsome discussion about the potential bias, how it might be operating and the potential impact on the analysis presented. Our response: We thank you for this comment. Indeed, the high rate of failure in the linkage with SNDS is an issue and it is necessary to deeply investigate its reasons. As you suggested we conducted a logistic regression analysis using the all factors from table 1 (excepted FDEP which was available only for patients successfully linked), followed by a stepwise to examine the statistical significance of these factors. The final model in the case of the FCCSS shows that the only factors that drive the linkage are actually the age in 2006 (OR: 1.014 95% CI 1.010 - 1.019) where at increasing age, patients were more likely to be linked; and death (OR: 0.392 95% CI 0.329 - 0.466) where the dead patients were less likely to be linked. For FRANCIM patients, only death was significant (OR: 0.472 95% CI 0.310 - 0.717). We did not find any role of the following factors: type of cancer or of the gender, age at diagnosis. This means that in both population patients, the identification variables (family and first name, sex, date and place of birth) included probably more error in death patients that in the other ones. Indeed, before 2000, most of this information was not computerized and the errors had more chances to be corrected, in routine, if the patients went frequently to the hospital, but no computerized information was transmitted to the hospital in case of death. This reason could also explains the role of age in 2006 in the FCCSS, which contains patients treated since to 1945, i.e. more long time ago as compared to the ones of FRANCIM Network: older the patient in 2006, the longer his has been treated, and more frequent were the errors in registrations . 5. It took me some time to consider the inclusion of the diagnoses in the early years (they start in 1945) given the observation window for the outcome only starts in 2011, but I think this approach is strong as it produces estimates across the age spectrum. Our response: We agree it is a strength of this FCCSS study that it allows an analysis across the age spectrum. 6. In the Primary Measures section, the authors indicate that the expenditures are expressed in real terms using the CPI. The authors need to be explicit in terms of the anchor year for the adjustment and provide a reference to the CPI data that was used for the adjustment. Our response: We have added more details on this point. Lines 169-171 “All expenditures were expressed in real terms using the consumer price index with a 2015 base year provided by the National Institute of Statistics and Economic Studies (INSEE).” 7. Given the longitudinal nature of the outcome ascertainment, I think it would strengthen the paper to provide the person-years of follow-up in all of the tables. Our response: Taking up your suggestion, we added Person-Year columns in Table 1 and Table S1 where patients’ characteristics are showed. 8. Given what appears to be skewed nature of the expenditures, it might be more appropriate to provide the median and IQR or both the mean and SD and median and IQR. Our response: We have added the median and IQR in Table 1. 9. There are two factors that likely drive 2 of the main results. The first is the higher costs among female survivors and the second is how death is related to higher costs. Neither of these are particularly surprising given births among female survivors are known to considerably contribute to health care costs. Is it possible for these costs to be removed for a sensitivity analysis so this could be examined? Further, could costs in the last period of life among those that die, say 6 or 8 weeks, be excluded so as to assess the timing of these costs relative to death?. Our response: We thank you for your suggestion. We agree about the high impact of death on costs. This is why we have performed 3 models in our multivariate analysis. One model included the death variable, the second one excluded it and the third model excluded patients who died (i.e. correspond to the sensitivity analysis required by the reviewer), in order to be able to appreciate the stability of our results (Table 4). In the first model (n=5319), we observed that "death" is an explanatory factor for expenditures (beta=1.85, p<0.0001), however, when this variable is removed from the model (model 2, n=5319) or when the model is run only on living people (n=5152), the estimators remain almost identical. So, we believe that dying does not seem to be a major confounding factor in the models Regarding pregnancy and childbirth, it seems very difficult to disentangle all pregnancy-related expenses because this would involve an exhaustive search of consultations, maternity leaves, medical procedures, drug codes, causes of hospitalization, in all the different information systems that are coded using different nomenclatures (ICD10, ATC Codes, medical procedures of French national health insurance, etc.). In order to reply to the questioning of the reviewer, we performed the following analysis: We have identified women who have been pregnant at least once, during study follow-up period, and we have re-estimated the models presented in Table 4, adding the dichotomous variable "pregnancy" yes/no, in order to evaluate the impact of this variable together with the sex variable. The results did not indicate that being pregnant was associated to higher costs (Coef: 0.0205 p-value: 0.8117) neither in the main model nor in the others models. This surprising could be due to the fact the costs of pregnancies could be counterbalanced by the fact that women who were pregnant were in a better health status (thus less expenditures) than the others. 10. In table 2 I struggle to make sense of the data presented. For example, consider paramedic, the annual mean expenditure per patient is presented as 12 so over the 6 year period of outcome assessment it would be 72. If I multiply this by the number of patients, 597, the total is 42,984 which is very different (by a factor of 10) than the 400,000 reported in the table. Why is this? Am I just miss-interpreting the table?. Our response: As you had pointed out there is a slight misunderstanding. Taking back your example, the annual mean expenditure per patient for Paramedic care is 12. This has been calculated as the division of the total expenditure divided by the number of years and divided by the total number of survivors (n=5319) and not only for those who have spent in paramedic care (n=597). The exact numbers for this example are 370,325 € / 6 / 5319 which is 11.6 and is rounded to 12 € in the tables presented. If we calculate the average expenditure for only the patients who spent on paramedic care this value rise up to 103,4 € which is very different and by almost a factor of 10. We believe that the important values to show the readers is the annual mean taking into account all survivors. Therefore, all figures in the column "Annual mean Per-Patient in €" correspond to the mean of all patients included in the study (n=5319). In order to do easier the understanding of the article, we added this information in a foot note of the table 2. Line 234 * Annual mean expenditure per-patient in € were calculated for the entire population (=5,319). 11. It would be good to include column percentages in table 3 so a reader could compare across groups. Our response: We have added the percentages in Table 3. 12. Please include more explicit column headings or notes to describe in the table. It is difficult to understand the table in the absence of reading the manuscript. Our response: We have added some foot notes in the tables in order to make them clearer. Reviewer #2: Thank you for the opportunity to review this manuscript. This is a population-based study of financial expenditures in registry-defined cohorts of childhood cancer survivors in France. The authors have documented the mean annual health system costs (i.e., excluding out of pocket expenses, etc.) from 2011-2016. The highest expenses were incurred for survivors of CNS tumors, survivors who were women and older during the study period. The data submitted are complete, statistical analyses correct, conclusions appropriate to results, and the paper is generally well-written. Please consider the following questions and comments, which are offered in hopes of strengthening this contribution: Our response: Thank you very much for your review and your helpful comments. 1. Would the authors please provide an explanation in the Introduction and/or Discussion why they did not include a non-cancer comparison group matched for age, sex, and age at diagnosis? This would provide some perspective for these results, which are limited to the childhood cancer population. Also, this would help elucidate what role "normal" health care costs played, such as pregnancy in female survivors. Our response: We fully agree that an analysis with a non-cancer comparison group would help to complete the results provided in this paper. However, at the time we carried out this study we did not have access to the data for the general French population or any other non-cancer comparison group. The processes to obtain this kind of data in France are slow and have been further delayed by COVID. Therefore, we could not take into account a non-cancer comparison group in our analysis. We have added this as a limitation of our study: Line 358-359 “However, our study is subject to some limitations. First of all, data on a comparison group without cancer were not available which limited our results to the CCS population. 1a. The analysis does include the two oncology cohorts, one from the FCCSS and the other from FRANCIM. A more complete explanation of how these two sources complement each other in interpreting the data would enhance the conclusions (i.e., what were authors hoping to discover by comparing these two cohorts?). Our response: Thank you very much for this comment. Indeed as said by the reviewer, we have hypothesized about the potential bias associated with the FCCSS because these patients were treated in Centers for the fight against cancer in France (French acronym: CLCC). These centers are dedicated to cancer treatment so we believe that they treat the most serious cancer patients or can provide a different kind of health care especially in pediatric patients (like survivors of the FCCSS) which would impact long-term patient outcomes and therefore be reflected in future costs. Our hypothesis then was that the FCCSS survivors would be patients with higher health care costs than other childhood cancer survivors treated in other facilities, because either they were more severe cases or they could have received more intense treatment that would leave more serious long-term late effects. We have made adjustments in the introduction to clarify this idea. Lines 87-95 “The French Childhood Cancer Survivor Study (FCCSS) which includes CCS treated before 2001 provides an opportunity to detail the overall healthcare expenditures among very long-term cancer survivors. Nevertheless, FCCSS survivors were treated during their childhood in Centers for the fight against cancer (CLCC) which are specialized hospitals in cancer treatment in France. Therefore, we hypothesize that the FCCSS could include patients with more advanced and/or aggressive cancers, or they may have received more innovative treatments and consequently differ in terms of long-term outcomes and future health expenses from other CCS treated in other hospital settings.” 2. Would the authors please explain why this sample was limited to solid tumors and excluded leukemias. Our response: The French Childhood Cancer Survivor Study (FCCSS) is a cohort built by the Radiation Epidemiology Team of CESP between 1985 and 1995 and concerns only people treated for a solid tumor or lymphoma. In France there is another cohort called The French Childhood Cancer Survivor Study for Leukemia (LEA) for survivors treated for leukemia which is coordinated by another group. To make this clear from the beginning we have stated in the title, abstract and study population section that is a study for solid cancer survivors. Line 2-4 “Health care expenditures among long-term solid childhood cancer survivors in France: Results from the French Childhood Cancer Survivor Study (FCCSS) and the French network of cancer registries (FRANCIM)”. Line 51-53 “A total of 5319 five-year solid CCS diagnosed before the age of 21 between 1945 and 2000 in France were identified in the French Childhood Cancer Survivors Study cohort (FCCSS) and the French cancer registry". Lines 104-105 “The FCCSS is a retrospective cohort of 7,670 five-year CCS diagnosed for solid cancer or lymphoma (all malignancies except leukemia)". Additionally, we added the following lines in the study population sections: Line 112-113 “Leukemia survivors from FRANCIM were excluded for better comparability with the FCCSS which did not include leukemia”. 3. For the expenditures listed in Table 2, it would be helpful to define these terms/categories, as some are not self-evident. For example, what are "sick payments"-? Presumably these terms are defined within the French system but the terms may be ambiguous for other national systems. Our response: We thank you for pointing out that some categories were not clear enough. We have changed the names of the following categories for a more accurate translation to make them clearer: Family medicine to “General practitioner visits” Medical Specialty to “Other specialist visits” Kinesiotherapy to “Physiotherapy visits” Nursing to “Nursing visits” Paramedic to “Other paramedic visits” Laboratory to “Laboratory test” Sick payments to “Sick leaves”. We have also added a footnote to better define “Technical Medical Procedures” and "Disability Benefits" in the Table 2: Lines 234-237 “**Technical medical procedures includes expenditures mainly related to medical imaging techniques. *** Disability benefits includes all welfare payments or pensions made by the French Government to assistance people with disabilities”. 4. Page 14, last paragraph, next to last line: a typographical error ("where" and should be "were"). Our response: We thank you for pointing out the mistake, the word has been changed. 5. For the regression analysis on tumor type, can the authors please explain in the manuscript why neuroblastoma was chosen as the referent? Our response: We have added more details in the statistical analysis section for the referent. Lines 191-193 “Neuroblastoma was chosen as the referent for type of primary cancer variable since was the most homogeneous group in medically terms." 6. Page 19, second paragraph, the sentence beginning, "Studies from the United States..." is difficult to understand. Are there some words missing? It is informative, but also rather long and hard to follow. Consider clarifying the language and also splitting it up into at least 2 smaller sentences. Our response: We agree that the wording was previously misleading. We clarified this as follows: Lines 310-315 “In the United States, CCS were more likely to have out-of-pocket medical costs [23], and up to 33% of them were unable to see a doctor or go to the hospital due to financial issues [24]. Annual medical expenditures in adolescent or young adult cancer survivors (age 15-35) has been estimated to $7,417 [25], while annual productivity loss among adult survivors of childhood (<14 years at diagnosis) cancer was estimated to $8,169 [8].” 7. In the Introduction, the authors suggest the analysis would address potential differences between patients cared for in the private vs. public health systems. Was this reported in the Results? Our response: We think there was a misunderstanding. The FCCSS cohort included patients treated in Centers for the fight against cancer (French acronym: CLCC) that are private non-profit health establishments of a university-hospital nature participating in the public hospital service in France. That means, they are financed by French health insurance and are controlled by the Ministry of Health, under the same conditions as public hospitals. Therefore we would not address the differences between patients cared for in the private vs. public hospital since all patients were treated in public establishments. We removed the words “private” and “public” from the introduction, and we clarified this as follows: Lines 90-91 “Nevertheless, FCCSS survivors were treated during their childhood in Centers for the fight against cancer (CLCC) which are specialized hospitals in cancer treatment in France.” ….. Line 94-95 “from other CCS treated in other hospital settings.” 8. Reference 27 does not have the year of publication. Our response: We thank you for pointing out the mistake, the reference has been updated. Lines 483-485 “27. Indelicato DJ, Bates JE, Mailhot Vega RB, Rotondo RL, Hoppe BS, Morris CG, et al. Second tumor risk in children treated with proton therapy. Pediatr Blood Cancer. 2021;68: e28941. doi:10.1002/pbc.28941" Submitted filename: Response to Reviewers.docx Click here for additional data file. 16 Mar 2022
PONE-D-21-17399R1
Health care expenditures among long-term solid childhood cancer survivors in France: Results from the French Childhood Cancer Survivor Study (FCCSS) and the French network of cancer registries (FRANCIM)
PLOS ONE Dear Dr. de Vathaire, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Apr 30 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript:
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5 Apr 2022 Dear Editor-in-chief, We are grateful to the editors and reviewers for their time and constructive comments on our manuscript. We have implemented their suggestions and answered their concerns which, we believe, allowed improving the manuscript. Changes in the initial version of the manuscript can be retrieved in the tracked change version. Below, we provide a point-by-point response explaining how we have addressed each of the editors or reviewers’ comments. We look forward to receiving your further evaluation of our manuscript. Sincerely, Florent de Vathaire, PhD Head of the Radiation Epidemiology Group Unit 1018 INSERM – CESP Institut Gustave Roussy 39, rue Camille Desmoulins 94805 Villejuif, France Tel: +33 1 42 11 54 57 Fax: +33 1 42 11 53 15 Email: florent.devathaire@gustaveroussy.fr Web: https://www.gustaveroussy.fr/ - https://cesp.inserm.fr/fr All page and line numbering below refers to the re-submitted clean copy, word document, which has been line numbered, before re-submission. Journal Requirements: Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. Our response: We thank the editor for your review. We have reviewed our reference list and have changed those that were found to be incorrect in order to fully meet PLOS ONE's style requirements. Specific changes were made in the references: Lines 401-403: “3. Freyer DR. Transition of Care for Young Adult Survivors of Childhood and Adolescent Cancer: Rationale and Approaches. J Clin Oncol. 2010;28: 4810–4818. doi:10.1200/JCO.2009.23.4278.” Lines 419-422: “9. Berger C, Casagranda L, Faure-Conter C, Freycon C, Isfan F, Robles A, et al. Long-Term Follow-up Consultation After Childhood Cancer in the Rhône-Alpes Region of France: Feedback From Adult Survivors and Their General Practitioners. J Adolesc Young Adult Oncol. 2017;6: 524–534. doi:10.1089/jayao.2017.0019.” Lines 471-473: “23. Nipp RD, Kirchhoff AC, Fair D, Rabin J, Hyland KA, Kuhlthau K, et al. Financial Burden in Survivors of Childhood Cancer: A Report From the Childhood Cancer Survivor Study. J Clin Oncol. 2017;35: 3474–3481. doi:10.1200/JCO.2016.71.7066.” Lines 509-512: “34. van Dorp W, Haupt R, Anderson RA, Mulder RL, van den Heuvel-Eibrink MM, van Dulmen-den Broeder E, et al. Reproductive Function and Outcomes in Female Survivors of Childhood, Adolescent, and Young Adult Cancer: A Review. J Clin Oncol. 2018;36: 2169–2180. doi:10.1200/JCO.2017.76.3441.” Lines 517-519: “36. Hjern A, Lindblad F, Boman KK. Disability in Adult Survivors of Childhood Cancer: A Swedish National Cohort Study. J Clin Oncol. 2007;25: 5262–5266. doi:10.1200/JCO.2007.12.3802.” Additional Editor Comments: Thank you for submitting your revised manuscript. Please consider the following additional comments in an additional revision and resubmission. 1. The wording of the revised title is awkward. Consider, "Healthcare expenditures among long-term survivors of pediatric solid tumors: Results from...." Our response: Taking up your suggestion, we have changed the title of the article to: “Healthcare expenditures among long-term survivors of pediatric solid tumors: Results from the French Childhood Cancer Survivor Study (FCCSS) and the French network of cancer registries (FRANCIM). 2. The response to Comment 5 of Reviewer 1 should include the addition of this strength of the FCCSS study (long follow-up) to the Discussion. Comment 5 – Reviewer 1. It took me some time to consider the inclusion of the diagnoses in the early years (they start in 1945) given the observation window for the outcome only starts in 2011, but I think this approach is strong as it produces estimates across the age spectrum. Our response: We have added more details regarding Comment 5 of Reviewer 1. Lines 359-360: “Another strength is the inclusion period starting in 1945, which allows us to study variations in cost across the age spectrum.” 3. The response to Comment 5 of Reviewer 2 is not clear and needs further explanation, including what is meant by the neuroblastoma group being "medically homogenous." Our response: We clarified this as follows: Lines 190-192: “Neuroblastoma was chosen as the referent for type of primary cancer variable since was one of the larger group of cancer of same histology”. 4. The term "paramedic" referring to costs needs clarification/definition. Our response: We thank you for pointing out that “paramedic” were not clear enough. We have changed the names of this category to “Other health professionals visits” which is a more accurate translation: We have also added a footnote to better define what’s included in the Table 2: † Other medical professional visits included expenditures related to visits to podiatrist, optometrists, speech therapist, and others. Submitted filename: Response to Reviewers.docx Click here for additional data file. 7 Apr 2022 Health care expenditures among long-term survivors of pediatric solid tumors: Results from the French Childhood Cancer Survivor Study (FCCSS) and the French network of cancer registries (FRANCIM) PONE-D-21-17399R2 Dear Dr. de Vathaire, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, David R Freyer Guest Editor PLOS ONE Additional Editor Comments (optional): Thank you for responding to the second round of comments, which have been satisfactorily addressed. Reviewers' comments: 16 May 2022 PONE-D-21-17399R2 Health care expenditures among long-term survivors of pediatric solid tumors: Results from the French Childhood Cancer Survivor Study (FCCSS) and the French network of cancer registries (FRANCIM) Dear Dr. de Vathaire: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. David R Freyer Guest Editor PLOS ONE
  38 in total

Review 1.  Transition of care for young adult survivors of childhood and adolescent cancer: rationale and approaches.

Authors:  David R Freyer
Journal:  J Clin Oncol       Date:  2010-03-29       Impact factor: 44.544

2.  The national healthcare system claims databases in France, SNIIRAM and EGB: Powerful tools for pharmacoepidemiology.

Authors:  Julien Bezin; Mai Duong; Régis Lassalle; Cécile Droz; Antoine Pariente; Patrick Blin; Nicholas Moore
Journal:  Pharmacoepidemiol Drug Saf       Date:  2017-05-24       Impact factor: 2.890

3.  Incidence and time trends of sarcoma (2000-2013): results from the French network of cancer registries (FRANCIM).

Authors:  Brice Amadeo; Nicolas Penel; Jean-Michel Coindre; Isabelle Ray-Coquard; Karine Ligier; Patricia Delafosse; Anne-Marie Bouvier; Sandrine Plouvier; Justine Gallet; Aude Lacourt; Gaëlle Coureau; Alain Monnereau; Simone Mathoulin-Pélissier; Emmanuel Desandes
Journal:  BMC Cancer       Date:  2020-03-06       Impact factor: 4.430

Review 4.  Value of a national administrative database to guide public decisions: From the système national d'information interrégimes de l'Assurance Maladie (SNIIRAM) to the système national des données de santé (SNDS) in France.

Authors:  P Tuppin; J Rudant; P Constantinou; C Gastaldi-Ménager; A Rachas; L de Roquefeuil; G Maura; H Caillol; A Tajahmady; J Coste; C Gissot; A Weill; A Fagot-Campagna
Journal:  Rev Epidemiol Sante Publique       Date:  2017-07-27       Impact factor: 1.019

5.  Long-Term Follow-up Consultation After Childhood Cancer in the Rhône-Alpes Region of France: Feedback From Adult Survivors and Their General Practitioners.

Authors:  Claire Berger; Léonie Casagranda; Cécile Faure-Conter; Claire Freycon; Florentina Isfan; Aurélie Robles; Béatrice Trombert-Paviot; Isabelle Guichard; Isabelle Durieu; Pascal Cathebras
Journal:  J Adolesc Young Adult Oncol       Date:  2017-05-25       Impact factor: 2.223

6.  Disability in adult survivors of childhood cancer: a Swedish national cohort study.

Authors:  Anders Hjern; Frank Lindblad; Krister K Boman
Journal:  J Clin Oncol       Date:  2007-11-20       Impact factor: 44.544

7.  Employment status and occupational level of adult survivors of childhood cancer in Great Britain: The British childhood cancer survivor study.

Authors:  Clare Frobisher; Emma R Lancashire; Helen Jenkinson; David L Winter; Julie Kelly; Raoul C Reulen; Michael M Hawkins
Journal:  Int J Cancer       Date:  2017-04-07       Impact factor: 7.396

8.  A detailed insight in the high risks of hospitalizations in long-term childhood cancer survivors-A Dutch LATER linkage study.

Authors:  Nina Streefkerk; Wim J E Tissing; Joke C Korevaar; Eline van Dulmen-den Broeder; Dorine Bresters; Margriet van der Heiden-van der Loo; Marry M van de Heuvel-Eibrink; Flora E Van Leeuwen; Jacqueline Loonen; Helena H J van der Pal; Cecile M Ronckers; A Brigitta Versluys; Andrica C H de Vries; Elizabeth A M Feijen; Leontine C M Kremer
Journal:  PLoS One       Date:  2020-05-19       Impact factor: 3.240

9.  Ecological association between a deprivation index and mortality in France over the period 1997 - 2001: variations with spatial scale, degree of urbanicity, age, gender and cause of death.

Authors:  Grégoire Rey; Eric Jougla; Anne Fouillet; Denis Hémon
Journal:  BMC Public Health       Date:  2009-01-22       Impact factor: 3.295

Review 10.  Reproductive Function and Outcomes in Female Survivors of Childhood, Adolescent, and Young Adult Cancer: A Review.

Authors:  Wendy van Dorp; Riccardo Haupt; Richard A Anderson; Renee L Mulder; Marry M van den Heuvel-Eibrink; Eline van Dulmen-den Broeder; H Irene Su; Jeanette Falck Winther; Melissa M Hudson; Jennifer M Levine; W Hamish Wallace
Journal:  J Clin Oncol       Date:  2018-06-06       Impact factor: 44.544
View more
  1 in total

1.  Long-term care, care needs and wellbeing of individuals after cancer in childhood or adolescence (VersKiK): study protocol of a large scale multi-methods non-interventional study.

Authors:  E Aleshchenko; E Swart; C Spix; M Voigt; P Trocchi; T Langer; G Calaminus; K Baust; J Glogner; P Ihle; J Küpper-Nybelen; C Lüpkes; T Kloppe; D Horenkamp-Sonntag; I Meier; U Marschall; P Dröge; M Klein; A Weiss; C Apfelbacher
Journal:  BMC Health Serv Res       Date:  2022-09-20       Impact factor: 2.908
  1 in total

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