Literature DB >> 34588616

Multicenter evaluation of breast cancer patients' satisfaction and experience with oncology telemedicine visits during the COVID-19 pandemic.

Alexandra Bizot1, Maryam Karimi2,3, Elie Rassy1, Pierre Etienne Heudel4, Christelle Levy5, Laurence Vanlemmens6, Catherine Uzan7, Elise Deluche8, Dominique Genet9, Mahasti Saghatchian10, Sylvie Giacchetti11, Juline Grenier12, Anne Patsouris13, Véronique Dieras14, Jean-Yves Pierga15, Thierry Petit16, Sylvain Ladoire17, William Jacot18, Marc-Antoine Benderra19, Anne De Jesus20, Suzette Delaloge1, Matteo Lambertini21,22, Barbara Pistilli23.   

Abstract

INTRODUCTION: During the COVID-19 pandemic, teleconsultation was implemented in clinical practice to limit patient exposure to COVID-19 while monitoring their treatment and follow-up. We sought to examine the satisfaction of patients with breast cancer (BC) who underwent teleconsultations during this period.
METHODS: Eighteen centres in France and Italy invited patients with BC who had at least one teleconsultation during the first wave of the COVID-19 pandemic to participate in a web-based survey that evaluated their satisfaction (EORTC OUT-PATSAT 35 and Telemedicine Satisfaction Questionnaire [TSQ] scores) with teleconsultation.
RESULTS: Among the 1299 participants eligible for this analysis, 53% of participants were undergoing standard post-treatment follow-up while 22 and 17% were currently receiving active anticancer therapy for metastatic and localised cancers, respectively. The mean satisfaction scores were 77.4 and 73.3 for the EORTC OUT-PATSAT 35 and TSQ scores, respectively. In all, 52.6% of participants had low/no anxiety. Multivariable analysis showed that the EORTC OUT-PATSAT 35 score correlated to age, anxiety score and teleconsultation modality. The TSQ score correlated to disease status and anxiety score.
CONCLUSION: Patients with BC were satisfied with oncology teleconsultations during the COVID-19 pandemic. Teleconsultation may be an acceptable alternative follow-up modality in specific circumstances.
© 2021. The Author(s), under exclusive licence to Springer Nature Limited.

Entities:  

Mesh:

Year:  2021        PMID: 34588616      PMCID: PMC8480754          DOI: 10.1038/s41416-021-01555-y

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


Introduction

Eighteen months after the coronavirus disease 2019 (COVID-19) pandemic began in China, the number of active cases that reached 145 million cases has placed significant strain on the medical community globally [1]. The rapidly growing case numbers have overwhelmed the health delivery systems and imposed unprecedented challenges to maintain essential healthcare services [2]. Unsurprisingly, cancer care was disrupted by the decreases and delays in detecting new cancers and delivering appropriate treatment [3]. Moreover, patients with cancer seem to be particularly vulnerable to severe complications of COVID-19 because of their immunosuppressive state induced by the malignancy and anticancer therapy [4, 5]. Multiple oncology societies have published consensus guidelines to amend cancer care and mitigate the negative effects of the COVID-19 pandemic [6-8]. Healthcare providers accommodated adjustments to compensate for these changes by minimising the number of hospital visits and preventing anticancer treatment-induced complications of COVID-19 [9, 10]. Many centres have adopted teleconsultation in daily practice to limit patient exposure to COVID-19 while monitoring their treatment and follow-up [11]. Teleconsultation is already implemented in USA and Northern European countries to ensure healthcare services across long distances, through the use of telecommunications and information technologies. During the past year, an expert consensus has favoured teleconsultation mainly among patients undergoing intravenous chemotherapies for early-stage breast cancer, receiving systemic treatments for metastatic breast cancer or during follow-up for breast cancer [12-14]. Given the knowledge gap in evaluating the preference of patients with this approach, we sought to examine the satisfaction of patients with breast cancer  who underwent teleconsultations during the COVID-19 pandemic.

Participants and methods

Study design

This prospective, observational, multicentric survey enrolled patients from April 6 to May 25, 2020 from 17 hospitals and cancer centres in France and 1 hospital in Italy. All patients with breast cancer, who were followed through at least one telehealth/at-phone visit during the COVID-19 pandemic, received by email the link to fill a one-time satisfaction questionnaire along with an information letter between 2 and 14 days after the teleconsultation. Each questionnaire was filled only once by each participant, according to the used Internet Protocol address. Neither reminders nor second invitations were sent to any of the participants. Therefore, patients who had multiple teleconsultations answered the questionnaire only once. The online questionnaire was completely anonymous. An information letter notified the participants that completing the questionnaire infers an inherent agreement to their participation in the study. The study was examined and approved by the internal review board at Gustave Roussy, Villejuif, France on April 6, 2020.

Questionnaire

The questionnaire was based on pre-existing validated scales and was designed into four sections after a comprehensive literature review. The first section enclosed seven items to collect information about the participants (age, family situation, accommodation type and region), the disease status (localised cancer, metastatic cancer, standard follow-up or other), teleconsultation situation (alone, as a couple, with family and other) and modality of teleconsultation (video or phone). The option “other” was included in some questions to allow participants to provide responses that were not defined in the listed answers. The second section included 11 items derived from the EORTC OUT-PATSAT 35 and focused on the physicians’ technical skills (knowledge, experience, assessment of physical symptoms), interpersonal skills (interest, willingness to listen), provision of information (about the disease, medical tests and treatment) and availability [15]. The corresponding French and Italian validated versions of the EORTC OUT-PATSAT 35 were used for this study. The items that were removed from the original EORTC OUT-PATSAT 35 questionnaire were those relevant to the nurse evaluation section and the physical environment organisation. The response format consisted of a five-point Likert scale: 1—poor, 2—fair, 3—good, 4—very good, and 5—excellent. The third section aimed to evaluate the satisfaction of the participants with the teleconsultation experience according to the 15-question Telemedicine Satisfaction Questionnaire (TSQ), which was initially validated in diabetic patients and recently in oncology patients [16, 17]. The TSQ was translated into French and Italian using the translation/back-translation method, a process through which the questionnaire is translated from English to French and Italian, and then it is translated back to English by a different translator who is unaware of the questionnaire’s initial wording in English. The English version was compared by the investigators for final approval. The third question of the TSQ was redundant in the EORTC OUT-PATSAT 35 and was consequently removed from the last version of the questionnaire. The response format consisted of a five-point Likert scale: 1—poor, 2—fair, 3—good, 4—very good, and 5—excellent. The fourth section used the Hospital Anxiety Depression Scale subscale for anxiety (HADS-A) to assess the patients’ anxiety and psychological distress associated with the global healthcare crisis [18, 19]. HADS-A is a validated 14-item scale, composed of 7 items assessing the intensity of anxiety and 7 items evaluating the intensity of depressive symptoms. For this study, only the 7 questions exploring patients’ anxiety were retained in the questionnaire. Each question was scored from 0 to 3, with a higher score reflecting a higher level of anxiety. Last, two items were added to reflect on the participants’ point of view on teleconsultation and its potential use in the future.

Statistical analysis

Descriptive statistics were used to describe the participants’ socio-demographic and clinical characteristics, with frequency and proportion for qualitative variables and mean and standard deviation (SD) for quantitative variables. The corresponding regions of each participant were categorised into COVID-19 hotspots and non-hotspots at the time of the survey (Regions Auvergne-Rhône-Alpes, Bourgogne-Franche-Comté, Grand-Est, Hauts-de-France, Ile de France from France and Liguria from Italy were considered as hotspots). The corresponding Likert score of the EORTC OUT-PATSAT 35 and TSQ items was linearly transformed to a 0–100 scale, with a higher score reflecting a higher level of satisfaction. The anxiety level (varying between 0 and 21 for each patient) was discretized into no/low anxiety, possible/minimal anxiety, anxiety and severe anxiety according to the HADS-A cutoffs at 7, 10 and 14, respectively. Spearman correlation was used to examine the correlation of the anxiety score (HADS-A) and satisfaction scales (EORTC OUT-PATSAT 35 and TSQ). We first investigated the values of satisfaction scales (EORTC OUT-PATSAT 35 and TSQ) across different characteristics (anxiety class, age class, disease status, accommodation type, family situation, teleconsultation situation and teleconsultation modality and region). Specifically, the mean value of each score (EORTC OUT-PATSAT 35 and TSQ) was calculated by performing univariable linear regression models with the score as the response variable and each characteristic as the explanatory variable. In order to evaluate the effect of each characteristic on the changes in the mean score (EORTC OUT-PATSAT 35 and TSQ), we performed multivariable linear regression models with the score as the response variable and all characteristics as explanatory variables. The linear regression coefficients obtained from these multivariable analyses represented the average adjusted contribution of each covariate to the score. Further, participants were categorised into two subsets according to the EORTC OUT-PATSAT 35 and TSQ scores; those scoring within the first quartile were assigned to the “poor satisfaction” group. A multivariable logistic regression model was used to investigate characteristics that were associated with a poor satisfaction score. Results were reported by odds ratios (ORs) and 95% confidence intervals (CIs). We considered a nominal significance level of 0.05. All statistical analyses were conducted using R V.3.6.2 in the RStudio environment.

Results

Patient socio-demographic and clinical characteristics

In total, 3722 patients were approached for inclusion and 2288 did not reply to the study invitation for unknown reasons. Of the 1434 participants (38.5%) who answered the questionnaire, 135 participants were excluded from the analysis for the following reasons: 100 participants did not complete all the items of the survey and hence 1 of the 3 score was missing, 35 participants did not report the age range, and 7 participants fell into the 2 categories. In total, 1299 participants were considered for the purpose of this study. The majority of participants were aged ≥50 years (n = 1042; 72.6%) and lived with their spouse or family members (n = 1100; 76.7%). Approximately half of the participants (n = 764; 53.3%) were undergoing standard post-treatment follow-up (with or without ongoing endocrine therapy) and the remaining were receiving anticancer therapy for metastatic and localised cancers (22.2 and 16.8%, respectively). The teleconsultations were predominantly by phone (n = 1294; 90.2%) and performed without the presence of a companion (n = 948; 68.6%) (Table 1). The clinical and socio-demographic characteristics of patients who used phone- and video-based teleconsultation are reported in Supplementary Table 1.
Table 1

Participants’ socio-demographic, clinical characteristics and scores.

Overall (N = 1434), n (%)France (N = 1338), n (%)Italy (N = 96), n (%)
Age in years<4092 (6.4)88 (6.5)4 (4.1)
40–49265 (18.5)241 (18.0)24 (25.0)
50–59418 (29.1)370 (27.7)48 (50.0)
60–69367 (25.6)351 (26.2)16 (16.7)
≥70257 (17.9)255 (19.1)2 (2.1)
(Missing)35 (2.4)33 (2.5)2 (2.1)
Accommodation typeApartment509 (35.5)442 (33.0)67 (69.8)
House915 (63.8)886 (66.2)29 (30.2)
Other10 (0.7)10 (0.7)0 (0.0)
RegionHotspots989 (69.0)896 (67.0)93 (96.9)
Non-hotspots445 (31.0)442 (33.0)3 (3.1)
Family situationAlone258 (18.0)249 (18.6)9 (9.4)
As a couple568 (39.6)551 (41.2)17 (17.7)
With family532 (37.1)469 (35.1)63 (65.6)
Other76 (5.3)69 (5.2)7 (7.3)
Disease statusLocalised cancer241 (16.8)217 (16.2)24 (25.0)
Metastatic cancer318 (22.2)316 (23.6)2 (2.1)
Standard follow-up764 (53.3)701 (52.4)63 (65.6)
Other111 (7.7)104 (7.8)7 (7.3)
Teleconsultation settingAlone984 (68.6)922 (68.9)62 (64.6)
Family429 (29.9)398 (29.7)31 (32.3)
Other21 (1.5)18 (1.3)3 (3.1)
Teleconsultation typeVideo140 (9.8)140 (10.5)0 (0.0)
Phone1294 (90.2)1198 (89.5)96 (100.0)
EORTC OUT-PATSAT 35 score (0–100)Mean (SD)77.4 (17.0)78.1 (16.7)67.6 (18.2)
(Missing)88835
TSQ score (0–100)Mean (SD)73.3 (15.5)73.4 (15.4)72.3 (16.5)
(Missing)89845
Hospital Anxiety Depression Scale subscale for anxiety (0–21)Mean (SD)7.2 (4.1)7.3 (4.1)6.7 (4.1)
(Missing)1061015
Hospital Anxiety Depression Scale subscale for anxiety (4 levels)No/low anxiety (HADS ≤ 7)754 (52.6)696 (52.0)58 (60.4)
Possible/minimal anxiety (8 ≤ HADS ≤ 10)296 (20.6)278 (20.8)18 (18.7)
Anxiety (11 ≤ HADS ≤ 14)204 (14.2)193 (14.4)11 (11.5)
Severe anxiety (15 ≤ HADS ≤ 21)74 (5.2)70 (5.2)4 (4.2)
(Missing)106 (7.4)101 (7.5)5 (5.2)

HADS Hospital Anxiety Depression Scale subscale for anxiety, n number of patients, SD standard deviation.

Participants’ socio-demographic, clinical characteristics and scores. HADS Hospital Anxiety Depression Scale subscale for anxiety, n number of patients, SD standard deviation.

Perceived satisfaction with telehealth visits

In the overall population, the mean scores were 77.4 (SD = 17.0), 73.3 (SD = 15.5) and 7.2 (SD = 4.1) for the EORTC OUT-PATSAT 35 score, TSQ score and HADS-A, respectively. Notably, almost half of the population experienced no/low anxiety (52.6% had HADS-A ≤ 7) and only 5.2% of the population had severe anxiety (HADS-A ≥ 15) (Table 1).

EORTC OUT-PATSAT 35 score

Univariable linear regression models showed significant differences in the mean EORTC OUT-PATSAT 35 score across anxiety levels with a lower mean among patients with severe anxiety compared to those with no/low anxiety (p < 0.01). The negative Spearman correlation coefficient between HADS-A as a continuous variable and EORTC OUT-PATSAT 35 score confirmed this finding (Supplementary Fig. 1). The results also showed differences in mean EORTC OUT-PATSAT 35 score across age groups (lower mean among groups 40–49 and 50–59 compared to younger patients) and teleconsultation modality (higher satisfaction level for those with video consultation compared to phone consultation) (Fig. 1). Multivariable analysis confirmed the significant association between EORTC OUT-PATSAT 35 score, anxiety level and teleconsultation modality. Differences in mean EORTC POUT-PATSAT 35 was found between “Possible anxiety” and “Severe anxiety” groups compared to “No/low anxiety” patients (β = −3.8, p = 0.001 and β = −5.9, p = 0.005, respectively). Lower mean satisfaction score was observed for those patients who performed the teleconsultation by phone compared to video consultation (β = −8.2, p < 0.001) (Table 2). Poor satisfaction was associated with severe anxiety compared to no/low anxiety, the odds of not being satisfied (in terms of EORTC OUT-PATSAT 35) increased by a factor of 2.1 compared to those with no/low anxiety (OR = 2.1, 95% CI 1.2–3.6). Being in the 40–49 or 50–59 age groups increased the odds of poor satisfaction by a factor of 2.2 and 2.3 compared to younger patients (<40 years) (OR = 2.2 [95% CI 1.1–4.3] and 2.3 [95% CI 1.2–4.4]). The results showed a significant association with the teleconsultation modality, as phone teleconsultations increased the odds of poor satisfaction by a factor of 2.7 compared to video consultations (OR = 2.7, 95% CI 1.5–4.9) (Table 3).
Fig. 1

Forest plot of the univariate analysis for the EORTC OUT-PATSAT 35 score distribution by different characteristic factors.

For each factors’ category, the point estimate of the mean score is represented by a bullet, and the vertical line represents the 2.5–97.5% CI of the score in that category. Within each factor, potential differences in mean score are tested using Student’s t test, setting the mean score in the first category as a reference (r). We report the corresponding p value above the boxplots for other groups. For readability, p values were coded as * for p values in (0.05, 0.01), ** for p values in (0.01, 0.001) and *** for p values.

Table 2

Mean (and SE) contribution of different factors to the EORTC OUT-PATSAT 35 and TSQ scores (multivariable analysis).

VariablesEORTC OUT-PATSAT 35TSQ
β (SE)p valueβ (SE)p value
Age class0.0570.27
 <40 yearsReferenceReference
 40–49 years−4.1 (2.1)0.054−2.2 (1.9)0.260
 50–59 years−3.7 (2.0)0.067−1.9 (1.8)0.310
 60–69 years−1.0 (2.1)0.6300.4 (1.9)0.840
 ≥70 years−0.8 (2.2)0.7300.1 (2.0)0.960
Accommodation type0.1200.360
 ApartmentReferenceReference
 House1.1 (1.1)0.2900.8 (1.0)0.390
 Other3.6 (6.4)0.5801.9 (5.8)0.740
Region0.3600.210
 Non-hotspotsReferenceReference
 Hotspots−0.96 (1.1)0.3601.2 (1.0)0.210
Family situation0.1500.100
 AloneReferenceReference
 As a couple1.2 (1.4)0.4202.2 (1.3)0.090
 With family2.9 (1.5)0.0602.9 (1.4)0.037
 Other2.5 (2.4)0.3003.3 (2.2)0.140
Disease status0.380<0.001
 Localised cancerReferenceReference
 Metastatic cancer−0.8 (1.3)0.5301.7 (1.2)0.150
 Standard follow-up1.5 (1.2)0.2003.5 (1.1)0.001
 Other1.2 (1.8)0.5205.0 (1.7)0.003
Anxiety score<0.001<0.001
 No/low anxietyReferenceReference
 Possible/minimal anxiety−3.8 (1.2)0.001−3.8 (1.1)<0.001
 Anxiety−2.5 (1.3)0.063−2.8 (1.2)0.022
 Severe anxiety−5.9 (2.1)0.005−6.4 (1.9)<0.001
Teleconsultation setting0.0680.300
 AloneReferenceReference
 Family1.3 (1.1)0.2500.2 (1.0)0.860
 Other−8.6 (4.5)0.053−6.2 (4.1)0.130
Teleconsultation type<0.001<0.001
 VideoReferenceReference
 Phone−8.2 (1.6)<0.001−6.0 (1.4)<0.001

SE standard error, TSQ Telemedicine Satisfaction Questionnaire. Statistically significant findings are marked in bold.

Table 3

Association between different factors and poor satisfaction EORTC OUT-PATSAT 35 and TSQ scores (multivariable analysis).

VariablesEORTC OUT-PATSAT 35TSQ
OR (95% CI)p valueOR (95%CI)p value
Age class0.0100.630
 <40 yearsReferenceReference
 40–49 years2.2 (1.1–4.3)0.0271.2 (0.7–2.3)0.510
 50–59 years2.3 (1.2–4.4)0.0171.3 (0.7–2.3)0.420
 60–69 years1.4 (0.7–2.8)0.3601.0 (0.5–1.9)0.960
 ≥70 years1.4 (0.7–2.8)0.3901.3 (0.6–2.4)0.510
Accommodation type0.510.290
 ApartmentReferenceReference
 House0.8 (0.6–1.1)0.2500.8 (0.6–1.1)0.150
 Other1.0 (0.2–5.6)0.9900.4 (0.05–3.9)0.460
Region0.7300.550
 Non-hotspotsReferenceReference
 Hotspots1.1 (0.8–1.4)0.7300.9 (0.7–1.2)0.550
Family situation0.2700.880
 AloneReferenceReference
 As a couple0.8 (0.5–1.2)0.3000.9 (0.6–1.4)0.720
 With family0.7 (0.4–1.0)0.0521.0 (0.6–1.5)0.880
 Other0.7 (0.4–1.4)0.2901.2 (0.6–2.4)0.590
Disease status0.250<0.001
 Localised cancerReferenceReference
 Metastatic cancer0.9 (0.6–1.4)0.7300.8 (0.6–1.2)0.300
 Standard follow-up0.7 (0.5–1.0)0.0520.5 (0.3–0.7)<0.001
 Other0.8 (0.5–1.4)0.4000.4 (0.2–0.8)0.010
Anxiety score0.039<0.001
 No/low anxietyReferenceReference
 Possible/minimal anxiety1.2 (0.9–1.7)0.2301.7 (1.2–2.4)0.001
 Anxiety1.2 (0.8–1.8)0.2701.5 (1.0–2.2)0.033
 Severe anxiety2.1 (1.2–3.6)0.0063.0 (1.7–5.0)<0.001
Teleconsultation setting0.7600.440
 AloneReferenceReference
 Family0.9 (0.7–1.3)0.7100.8 (0.6–1.1)0.200
 Other1.4 (0.5–4.4)0.5501.0 (0.3–3.4)0.990
Teleconsultation type<0.0010.210
 VideoReferenceReference
 Phone2.7 (1.5–4.9)<0.0011.4 (0.8–2.3)0.210

CI confidence interval, OR odds ratio, TSQ Telemedicine Satisfaction Questionnaire. Statistically significant findings are marked in bold.

Forest plot of the univariate analysis for the EORTC OUT-PATSAT 35 score distribution by different characteristic factors.

For each factors’ category, the point estimate of the mean score is represented by a bullet, and the vertical line represents the 2.5–97.5% CI of the score in that category. Within each factor, potential differences in mean score are tested using Student’s t test, setting the mean score in the first category as a reference (r). We report the corresponding p value above the boxplots for other groups. For readability, p values were coded as * for p values in (0.05, 0.01), ** for p values in (0.01, 0.001) and *** for p values. Mean (and SE) contribution of different factors to the EORTC OUT-PATSAT 35 and TSQ scores (multivariable analysis). SE standard error, TSQ Telemedicine Satisfaction Questionnaire. Statistically significant findings are marked in bold. Association between different factors and poor satisfaction EORTC OUT-PATSAT 35 and TSQ scores (multivariable analysis). CI confidence interval, OR odds ratio, TSQ Telemedicine Satisfaction Questionnaire. Statistically significant findings are marked in bold.

TSQ score

Univariable regressions showed a lower mean TSQ score among patients with “Possible anxiety”, “Anxiety” and “Severe anxiety” compared to those with no/low anxiety (p < 0.05). The results showed a higher mean TSQ score for those with video consultation compared to phone consultations (p < 0.001) (Fig. 2). Multivariable analysis showed significant associations between TSQ score and anxiety level, as well as disease status and teleconsultation modality. Differences in mean TSQ was observed between “Possible anxiety”, “anxiety” and “Severe anxiety” groups compared to “No/low anxiety” patients (β = −3.8, p < 0.001, β = −2.8, p = 0.022 and β = −6.4, p < 0.001, respectively) (Table 2). In terms of TSQ, the odds of not being satisfied among those with severe anxiety increased by a factor of 3.0 compared to those with no/low anxiety (OR = 3.0, 95% CI 1.7–5.0). The disease status was significantly associated with poor satisfaction, and those with standard follow-up were more satisfied than those with localised cancer (OR = 0.5, 95% CI 0.3–0.7) (Table 3).
Fig. 2

Forest plot of the univariate analysis for the TSQ score distribution by different characteristic factors.

For each factors’ category, the point estimate of the mean score is represented by a bullet, and the vertical line represents the 2.5–97.5% CI of the score in that category. Within each factor, potential differences in mean score are tested using Student’s t test, setting the mean score in the first category as a reference (r). We report the corresponding p value above the boxplots for other groups. For readability, p values were coded as * for p values in (0.05, 0.01), ** for p values in (0.01, 0.001) and *** for p values.

Forest plot of the univariate analysis for the TSQ score distribution by different characteristic factors.

For each factors’ category, the point estimate of the mean score is represented by a bullet, and the vertical line represents the 2.5–97.5% CI of the score in that category. Within each factor, potential differences in mean score are tested using Student’s t test, setting the mean score in the first category as a reference (r). We report the corresponding p value above the boxplots for other groups. For readability, p values were coded as * for p values in (0.05, 0.01), ** for p values in (0.01, 0.001) and *** for p values.

Discussion

As the first wave of the COVID-19 pandemic has disrupted healthcare systems across the world including France and Italy, many cancer centres have opted to limit hospital visits and meetings whenever possible [20, 21]. Multidisciplinary meetings were maintained in a videoconference format to reduce the contact between healthcare professionals, which has been widely accepted among physicians involved in the management of breast cancer [22]. Patient visits were transformed to teleconsultations in many instances but the patient satisfaction with this consultation format was not reported [23]. This study provides a snapshot of the satisfaction of patients with breast cancer undergoing teleconsultation instead of in-person visits through an online questionnaire addressed to participants by email. In our experience, patients were predominantly aged >50 years (72.6%), undergoing standard follow-up (53.3%) and living in hotspot regions (69%). With the rapid spread of the COVID-19 pandemic, most in-person visits were switched to teleconsultations on short notice. Nevertheless, the anxiety scale system showed relatively low scores with almost half of the participants presenting no/low anxiety (HADS-A ≤ 7). The EORTC OUT-PATSAT 35 and TSQ scores were considerably high and suggestive that the majority of the participants had a positive experience with teleconsultations. The lack of clinical breast exam is worrying for many patients, as outlined in the answers to the last two items of the questionnaire. Our findings adjusted for confounding factors showed that the two satisfaction scores correlated to the anxiety score. A meta-analysis of 2190 women with breast cancer showed a similar anxiety score between telehealth interventions and in-person visits; it associated telehealth intervention with a higher quality of life and self-efficacy as well as less depression and perceived stress [24]. The poor satisfaction EORTC OUT-PATSAT 35 score correlated to age and teleconsultation modality. Elderly patients are not commonly favourable to the use of technological tools to communicate medical results, which may impact the difference in video or phone preferences [25, 26]. The poorer satisfaction of TSQ correlated mainly to disease status. The TSQ score was significantly lower among patients in follow-up for whom it is potentially more important to meet physically with their oncologists because of the less frequent consultations. The partially nonreproducible correlation findings between the two satisfaction scores may be explained by the fact that EORTC OUT-PATSAT 35 mainly evaluates the global satisfaction with the health system, whereas TSQ is more specific and only related to telehealth itself. Surprisingly, the two satisfaction scores were not associated with living in COVID-19 hotspots or not, keeping in mind that the study was conducted before the widespread of COVID-19 vaccines. In 2011, breast cancer survivors participating in a general survivorship survey considered that teleconsultation had a less favourable impact on cancer survival and cancer-related worrying compared to in-person visits [27]. On the other hand, several randomised trials have reported high satisfaction scores among patients with breast cancer undergoing nurse-led teleconsultations by phone and in-person visits before the COVID-19 pandemic [28-31]. Participants were satisfied with the interpersonal aspects, emotional functioning and feeling of control and anxiety [28-31]. The clinical implication of teleconsultations was also evaluated in a randomised trial of 374 women with breast cancer [30]. It showed that teleconsultations had higher levels of satisfaction compared to face-to-face consultations and were not shown to increase the anxiety level despite omitting clinical examinations. The time to detection of the few recurrences encountered (4.5%) was not statistically different between traditional consults and teleconsultation by phone (60.5 vs 39.0 days; p = 0.228). Notably, the number of clinical investigations did not differ between the two groups albeit the lack of visual cues [30]. Another clinical implication of teleconsultation may be the limited evidence supporting informed drug adherence in this setting, as reflected in the management of osteoporosis [32]. There are several limitations inherent to the design of this study. First, the patient population may not represent the whole population of patients with breast cancer undergoing cancer care given that the majority consulted tertiary cancer centres. Second, many patients appreciated teleconsultation to avoid long travel distances and hospital exposure and transmission risk of COVID-19 [33, 34]. However, the satisfaction with teleconsultation may be biased by several factors that were not directly measured. For instance, many elderly patients lacked any experience in using video-based teleconsultation, had hearing and cognitive difficulties and had inaccessibility to the results of biologic tests and imaging, which may result in negative feedback relative to teleconsultation [35, 36]. In line with previously published data [37], patients who opted for video-based teleconsultations were younger, lived with their families and had localised disease (Supplementary Table 1). Consultation reimbursements did not impact the implementation of either teleconsultation modalities, namely by phone or video-based call. Both phone- and video-based modalities were fully covered in France by the French Health Insurance organisation since the beginning of the pandemic [38], whereas neither modality was reimbursed in Italy at the time of the present survey [39]. In comparison to in-patient visit, published data showed that teleconsultations were shorter, had fewer instances of problems raised by patients and scored lower on consultation quality items [40]. Furthermore, our findings may be biased by a preponderance of patients who were likely experienced with the internet given that our invitations were addressed by email. Last, all items were self-collected, thus some items may not be completely accurate, in particular regarding disease stage assessment. In conclusion, our findings suggest that patients with breast cancer were globally satisfied with teleconsultation during the first wave of the COVID-19 pandemic. With high satisfaction scores and a substantial reduction in hospital visits, teleconsultation may be an acceptable alternative follow-up modality in special circumstances. The economic evaluation of follow-up strategies after curative treatment for breast cancer considered that teleconsultations can be an appropriate cost-effective alternative to in-person visits after treatment completion [41]. Teleconsultations may reduce the burden on busy hospitals, especially during the pandemic, but do not necessarily lead to cost savings [42]. Although in-person visits remain the standard practice given the access to clinical examination, medical tests and imaging review and interpersonal relation between the oncologist and the patient, teleconsultations should be further evaluated to better identify the patients who are suitable for this strategy in special circumstances. Beyond organisation and satisfaction, high-level medical validation of their quality and adequacy is foundational before implementing structured teleconsultations in clinical practice. Our study is a first step that identifies populations more prone to accept and be satisfied with this approach. Further steps should describe the general mix of different consult modalities and compare the satisfaction score of in-person visits and teleconsultations by phone- or video-based calls. Extended Table Supplementary material Extended Figure 1 Checklist signed
  27 in total

1.  Telehealth in Oncology During the COVID-19 Outbreak: Bringing the House Call Back Virtually.

Authors:  Raymond Liu; Tilak Sundaresan; Mary E Reed; Julia R Trosman; Christine B Weldon; Tatjana Kolevska
Journal:  JCO Oncol Pract       Date:  2020-05-04

Review 2.  Caring for patients with cancer in the COVID-19 era.

Authors:  Joris van de Haar; Louisa R Hoes; Charlotte E Coles; Kenneth Seamon; Stefan Fröhling; Dirk Jäger; Franco Valenza; Filippo de Braud; Luigi De Petris; Jonas Bergh; Ingemar Ernberg; Benjamin Besse; Fabrice Barlesi; Elena Garralda; Alejandro Piris-Giménez; Michael Baumann; Giovanni Apolone; Jean Charles Soria; Josep Tabernero; Carlos Caldas; Emile E Voest
Journal:  Nat Med       Date:  2020-04-16       Impact factor: 53.440

3.  Assessing the Impact of the COVID-19 Outbreak on the Attitudes and Practice of Italian Oncologists Toward Breast Cancer Care and Related Research Activities.

Authors:  Francesca Poggio; Marco Tagliamento; Massimo Di Maio; Valentino Martelli; Andrea De Maria; Emanuela Barisione; Marco Grosso; Francesco Boccardo; Paolo Pronzato; Lucia Del Mastro; Matteo Lambertini
Journal:  JCO Oncol Pract       Date:  2020-06-23

4.  What the oncologist needs to know about COVID-19 infection in cancer patients.

Authors:  Elie Rassy; Rita-Maria Khoury-Abboud; Nathalie Ibrahim; Clarisse Kattan; Tarek Assi; Joseph Kattan
Journal:  Future Oncol       Date:  2020-04-23       Impact factor: 3.404

5.  [COVID-19 and people followed for breast cancer: French guidelines for clinical practice of Nice-St Paul de Vence, in collaboration with the Collège Nationale des Gynécologues et Obstétriciens Français (CNGOF), the Société d'Imagerie de la Femme (SIFEM), the Société Française de Chirurgie Oncologique (SFCO), the Société Française de Sénologie et Pathologie Mammaire (SFSPM) and the French Breast Cancer Intergroup-UNICANCER (UCBG)].

Authors:  Joseph Gligorov; Thomas Bachelot; Jean-Yves Pierga; Eric-Charles Antoine; Corinne Balleyguier; Emmanuel Barranger; Yazid Belkacemi; Hervé Bonnefoi; François-Clément Bidard; Luc Ceugnart; Jean-Marc Classe; Paul Cottu; Charles Coutant; Bruno Cutuli; Florence Dalenc; Emile Darai; Veronique Dieras; Nadine Dohollou; Sylvie Giacchetti; Anthony Goncalves; Anne-Claire Hardy-Bessard; Gilles Houvenaeghel; Jean-Philippe Jacquin; William Jacot; Christelle Levy; Carole Mathelin; Israel Nisand; Thierry Petit; Thierry Petit; Edouard Poncelet; Sofia Rivera; Roman Rouzier; Rémy Salmon; Florian Scotté; Jean-Philippe Spano; Catherine Uzan; Laurent Zelek; Marc Spielmann; Frédérique Penault-Llorca; Moise Namer; Suzette Delaloge
Journal:  Bull Cancer       Date:  2020-04-01       Impact factor: 1.276

6.  COVID-19 in patients with cancer: managing a pandemic within a pandemic.

Authors:  Leora Horn; Marina Garassino
Journal:  Nat Rev Clin Oncol       Date:  2021-01       Impact factor: 66.675

Review 7.  A Practical Approach to the Management of Cancer Patients During the Novel Coronavirus Disease 2019 (COVID-19) Pandemic: An International Collaborative Group.

Authors:  Humaid O Al-Shamsi; Waleed Alhazzani; Ahmad Alhuraiji; Eric A Coomes; Roy F Chemaly; Meshari Almuhanna; Robert A Wolff; Nuhad K Ibrahim; Melvin L K Chua; Sebastien J Hotte; Brandon M Meyers; Tarek Elfiki; Giuseppe Curigliano; Cathy Eng; Axel Grothey; Conghua Xie
Journal:  Oncologist       Date:  2020-04-27

8.  Delivering Cancer Care During the COVID-19 Pandemic: Recommendations and Lessons Learned From ASCO Global Webinars.

Authors:  Abdul Rahman Jazieh; Stephen L Chan; Giuseppe Curigliano; Natalie Dickson; Vanessa Eaton; Jesus Garcia-Foncillas; Terry Gilmore; Leora Horn; David J Kerr; Jeeyun Lee; Clarissa Mathias; Angélica Nogueira-Rodrigues; Lori Pierce; Alvaro Rogado; Richard L Schilsky; Jean-Charles Soria; Jeremy L Warner; Kazuhiro Yoshida
Journal:  JCO Glob Oncol       Date:  2020-09

9.  Managing cancer patients during the COVID-19 pandemic: an ESMO multidisciplinary expert consensus.

Authors:  G Curigliano; S Banerjee; A Cervantes; M C Garassino; P Garrido; N Girard; J Haanen; K Jordan; F Lordick; J P Machiels; O Michielin; S Peters; J Tabernero; J Y Douillard; G Pentheroudakis
Journal:  Ann Oncol       Date:  2020-07-31       Impact factor: 32.976

10.  Are overwhelmed health systems an inevitable consequence of covid-19? Experiences from China, Thailand, and New York State.

Authors:  Viroj Tangcharoensathien; Mary T Bassett; Qingyue Meng; Anne Mills
Journal:  BMJ       Date:  2021-01-22
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  6 in total

1.  Breast Medical Oncologists' Perspectives of Telemedicine for Breast Cancer Care: A Survey Study.

Authors:  Eleni Stavrou; Jeanna Qiu; Affan Zafar; Angela C Tramontano; Steven Isakoff; Eric Winer; Deborah Schrag; Christopher Manz
Journal:  JCO Oncol Pract       Date:  2022-06-07

2.  The impact of the COVID-19 pandemic on perceived access to health care and preferences for health care provision in individuals (being) treated for breast cancer.

Authors:  Dieuwke R Mink van der Molen; Claudia A Bargon; Marilot C T Batenburg; Lilianne E van Stam; Iris E van Dam; Inge O Baas; Miranda F Ernst; Wiesje Maarse; Maartje Sier; Ernst J P Schoenmaeckers; Thijs van Dalen; Rhodé M Bijlsma; Annemiek Doeksen; Femke van der Leij; Danny A Young-Afat; Helena M Verkooijen
Journal:  Breast Cancer Res Treat       Date:  2021-12-01       Impact factor: 4.624

Review 3.  The evolving scenario of cancer care provision across the COVID-19 pandemic in Europe.

Authors:  Marco Tagliamento; Francesca Poggio; Marta Perachino; Chiara Pirrone; Piero Fregatti; Matteo Lambertini
Journal:  Curr Opin Support Palliat Care       Date:  2022-07-15       Impact factor: 2.265

4.  Bio-ethical issues in oncology during the first wave of the COVID-19 epidemic: A qualitative study in a French hospital.

Authors:  Henri-Corto Stoeklé; Laure Ladrat; Terence Landrin; Philippe Beuzeboc; Christian Hervé
Journal:  J Eval Clin Pract       Date:  2022-09-15       Impact factor: 2.336

5.  Lessons for Oncology From the COVID-19 Pandemic: Operationalizing and Scaling Virtual Cancer Care in Health Systems.

Authors:  Thomas J Roberts; Inga T Lennes
Journal:  Cancer J       Date:  2022 Mar-Apr 01       Impact factor: 2.074

Review 6.  A Narrative Review of the Launch and the Deployment of Telemedicine in Italy during the COVID-19 Pandemic.

Authors:  Daniele Giansanti; Giovanni Morone; Alice Loreti; Marco Germanotta; Irene Aprile
Journal:  Healthcare (Basel)       Date:  2022-02-23
  6 in total

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