The impact of chronic comorbidities at the time of breast cancer diagnosis on quality of life, and emotional health following treatment in Canada.

INTRODUCTION: Advances in breast cancer screening and treatment have led to an increasing number of breast cancer survivors. The objective of this study was to determine the impact of comorbidities on self-reported quality of life (QOL) and emotional health following a breast cancer diagnosis and treatment.
METHODS: Women with a personal history of breast cancer (N = 3,372) were identified from the cross-sectional Canadian Partnership Against Cancer (CPAC) Experiences of Cancer Patients in Transitions Survey. Multinomial (nominal) logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the relationship between burden of comorbidities and overall QOL and emotional health (very poor/poor, fair, good, very good).
RESULTS: Of the 3,372 participants, 57% reported at least one chronic condition at the time of breast cancer diagnosis. As the number of chronic conditions at diagnosis increased, the odds of reporting worse quality of life and emotional health following treatment also increased. Specifically, compared to women reporting very good QOL, for each additional chronic condition, women reported significantly higher odds of reporting good (OR = 1.22, 95% CI: 1.12, 1.32), fair (OR = 1.76, 95% CI: 1.58, 1.96), or poor/very poor (OR = 2.31, 95% CI: 1.86, 2.88) QOL. Similarly, for each additional comorbidity, women reported significantly higher odds of reporting good (OR = 1.17, 95% CI: 1.07, 1.28), fair (OR = 1.63, 95% CI: 1.46, 1.82), or poor/very poor (OR = 2.17, 95% CI: 1.81, 2.60) emotional health, relative to very good emotional health.
CONCLUSION: Breast cancer survivors coping with a high comorbidity burden experience worse overall QOL and emotional health following treatment. This highlights the importance of integrating information on comorbidities into survivorship care to improve the experience and overall outcomes of patients with complex needs.

Introduction

Breast cancer is the most common cancer diagnosed among North American women, with 1 in 8 expected to develop the disease in their lifetime [1]. Advances in breast cancer screening and treatment have led to an increasing number of breast cancer survivors. As 5-year net survival for breast cancer in Canada approaches 90% [1], addressing the needs of these women and emphasizing the improvement of overall quality of life (QOL) is increasingly important.

In Canada, 83% of breast cancer cases occur in women over 50 years of age [2, 3], therefore the majority of survivors are older women. Chronic comorbidities (e.g., pulmonary disease, and dementia) are common in 20–35% of breast cancer patients, and their prevalence can be as high as 86% in patients aged 65 and above [4]. Presence of comorbidities at the time of diagnosis can negatively impact survival after breast cancer diagnosis, especially in these women [5, 6]. Prior work has shown that breast cancer survivors with any comorbidity have a significantly higher all-cause and breast cancer-specific mortality [7]. Furthermore, improvements in breast cancer survival witnessed over the past three decades have not been observed in breast cancer patients with severe comorbidities [7, 8].

QOL is a multidimensional measure encompassing physical, mental, social, economic, and spiritual aspects. As such, QOL is impacted by a multitude of factors. Socioeconomic factors, including social isolation [9], low socioeconomic status [9, 10], and lower neighborhood or household level income [11, 12] have been found to be associated with poorer QOL among breast cancer survivors. Conversely, greater social support [13], and support satisfaction [14] have a positive impact on QOL.

In breast cancer survivors, QOL is also inextricably linked to survival. In a cohort of women over 65 years of age with early-stage breast cancer, health related QOL measures predicted 10-year mortality independently of traditional breast cancer prognostic variables [4], suggesting that interventions aimed at improving physical function, mental health, and social support might improve both health related QOL and survival. Further, young breast cancer survivors (i.e., age ≤45 years) frequently report worse QOL [15], often stemming from menopausal symptoms, problems with relationships, and sexual functioning [16]. Premenopausal breast cancer survivors have been known to experience decreased emotional wellbeing, increased anxiety and body image issues [17].

In order to improve quality of life and overall survival among breast cancer survivors in Canada, the impact of comorbidity burden on both QOL and emotional well-being warrants examination [18]. The objective of this study was to leverage a large pan-Canadian survey of cancer survivors to determine the association between the comorbidity burden—as captured by the number of chronic conditions at the time of diagnosis, and both self-reported QOL and emotional health following treatment for breast cancer.

Materials and methods

Data sources

The data for this study were obtained from the Experiences of Cancer Patients in Transitions Study (Transitions Study), a cross-sectional study of adult cancer survivors over the age of 18 years, conducted by the Canadian Partnership Against Cancer (CPAC). The goal of this study was to better understand challenges related to cancer survivorship. A comprehensive description of survey methods, development, validation, and dissemination have been published elsewhere [19, 20]. Briefly, in 2016, 40,790 survey packages were mailed to adolescent and adult cancer patients identified through the provincial cancer agencies/registries of 10 Canadian provinces. This included survivors of breast, colorectal, prostate, melanoma, and hematological cancers who completed treatment (chemotherapy, radiation therapy, surgical treatment, or a combination of these therapies) in the previous 1–3 years. Data were collected in parallel across the 10 provinces, with the recruitment period ranging from 8 to 19 weeks for different provinces. The study population was selected through probability sampling. A sampling error margin of ±5% for the 95% CI was used to calculate the sample size for each disease site and province, assuming a response rate of 30% [19]. In smaller provinces, where the desired precision was not achieved, all eligible survivors were interviewed [19], which—combined with recruitment through provincial cancer agencies—minimized selection bias. In total, 13,319 responses were received, corresponding to a response rate of 33%.

The data used in this study are in the public domain and available through the CPAC website [21]. The authors were not involved in any aspect of the original study and did not have access to any identifying information associated with the data. This study was from ethics review. Results are reported in accordance with the STROBE statement [22], (see STROBE checklist, S1 File).

Exposure and outcomes

The Transitions Study survey captured personal and demographic characteristics; needs as a cancer survivor (physical, emotional, informational, and practical); and enablers and barriers of these needs being met. It also collected data on the prevalence of chronic conditions at the time of breast cancer diagnosis. This included: 1) arthritis, osteoarthritis, or other rheumatic disease, 2) cardiovascular or heart condition, hypertension or high blood pressure, 3) chronic kidney disease, 4) diabetes, 5) osteoporosis, 6) respiratory diseases (e.g., asthma or COPD—chronic obstructive pulmonary disease) and 7) mental health issues (e.g., depression or anxiety), with a free text field for other chronic conditions. The number of chronic conditions a participant reported was defined as the sum of the 6 most prevalent chronic conditions (>8% prevalence in breast cancer survivors). Specifically, these included: arthritis, cardiovascular disease, diabetes, osteoporosis, respiratory illness, and mental health issues.

Overall QOL was assessed at the time of the survey i.e. after treatment completion, using the following question: “How would you describe your overall quality of life today?” Emotional health was assessed similarly using the question, “In general, would you say your emotional health is…”. Both variables were assessed using a Likert scale of very poor, poor, fair, good, very good. The Transitions Study collected data on overall QOL, a broad and multidimensional concept. Prior literature [23, 24] has focused specifically on health related quality of life, which is a patient reported outcome, usually measured using multi-item surveys such as the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 30 (QLQ-C30), or the Short Form Health Survey (SF-36 for the 36 item version of the survey). The QOL measure included in the CPAC Transitions Study questionnaire is comparable the global QOL measure from the EORTC QLQ-C30, which has been validated for use in breast cancer patients [25-27].

Study population

Of the 13,319 Transitions Study survey respondents, N = 3,729 women over the age of 30 years reported having a personal history of breast cancer. This was assessed by asking women about their most recent cancer diagnosis. For 330 women, (9.8%) the index cancer was not their first cancer diagnosis. Individuals with missing data on age at data collection (N = 9), QOL (N = 6), and emotional health (N = 115) were excluded. Women with missing data on covariates (education [n = 123, 3.4%], household size [n = 8, 0.2%], employment status [n = 111, 3.1%], marital status [n = 27, 0.8%], and whether a physician was in charge of their follow-up care [n = 13, 0.4%]), were also excluded leaving a final study population of 3,372 women for the current analysis (Fig 1).

Fig 1

Sample size: Flow diagram of Transitions Study survey respondents included in the analysis.

Statistical analysis

Generalized logit models were used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the relationship between number of chronic conditions (continuous) and self-reported QOL and emotional health (very poor/poor, fair, good, very good). Models were adjusted for a priori selected variables, including, age, education, employment status, marital status, household size, and whether participants had a healthcare provider such as a nurse or physician in charge of overseeing their follow up care. Variable coding details are presented in S1 Table. Statistical significance was determined at an alpha level of 0.05. All analyses were conducted using SAS version 9.4 (Cary, NC).

Results

Demographic and physical health characteristics of the study population are reported in Table 1. Most respondents were between 65–74 years of age (32%), had a post-secondary degree (57%) and were married or partnered (71%). More than half of the participants were retired (55%) and lived in a two-person household (56%). Almost all participants had a physician in charge of overseeing their follow-up care (97%). On average, participants had one chronic condition (interquartile range 0–2), and most participants reported one or more chronic condition at the time of breast cancer diagnosis (57%). The most prevalent chronic condition was arthritis (32%), followed by cardiovascular disease (25%). Notably, women with fewer comorbidities (<4) tended to receive more treatments than those with a higher burden of comorbidities (≥ 4). This was particularly true for chemotherapy (45% vs 35% for women with <4 vs. ≥ 4 comorbidities.

Table 1

Demographic characteristics of the breast cancer survivors in the Transitions Study, N = 3,372.

	N (%) a
DEMOGRAPHIC CHARACTERISTICS
Age (years)
30–34	34 (1.0)
35–44	142 (4.2)
45–54	555 (16.5)
55–64	984 (29.2)
65–74	1,078 (32.0)
75–84	473 (14.0)
≥ 85	106 (3.1)
Education
High School or Less	1,206 (35.8)
Post-Secondary Degree	1,931 (57.3)
Graduate School	235 (7.0)
Income
< $25,000	439 (13.0)
$25,000 to < $50,000	729 (21.6)
$50,000 to < $75,000	549 (16.3)
$75,000 or more	847 (25.1)
Missing	808 (24.0)
Employment Status
Employed (full time/part time)	1,133 (33.6)
Unemployed, homemaker, student, or on paid sick leave	371 (11.0)
Retired	1,868 (55.4)
Marital Status
Single	198 (5.9)
Married, or partnered	2,390 (70.9)
Divorced, separated, or widowed	784 (23.3)
Household Size
1 (Live Alone)	735 (21.8)
2	1,898 (56.3)
3	374 (11.1)
4	242 (7.2)
5 or More	123 (3.7)
Physician in Charge of Follow-up
Yes	3,263 (96.8)
No or Unsure	109 (3.2)
CHRONIC CONDITIONS
Arthritis
No	2,297 (68.1)
Yes	1,075 (31.9)
Cardiovascular Disease
No	2,522 (74.8)
Yes	850 (25.2)
Diabetes
No	3,092 (91.7)
Yes	280 (8.3)
Osteoporosis
No	3,086 (91.5)
Yes	286 (8.5)
Respiratory Diseases
No	3,086 (91.5)
Yes	286 (8.5)
Mental Health Issues
No	2,954 (87.6)
Yes	418 (12.4)
Number of Chronic Conditions
Median (Interquartile Range)	1 (0, 2)
0	1,455 (43.1)
1	1,015 (30.1)
2	604 (17.9)
3	229 (6.8)
4	61 (1.8)
5	7 (0.2)
6	1 (0.0)

Abbreviations: N = number.

aPercentages may add up to 100% in some cases due to rounding.

Most participants rated their QOL as very good (40%) or good (44%); with only 14% of participants reporting a fair QOL, and 2% reporting a poor or very poor QOL (Table 2). As women’s reported number of chronic conditions increased, their odds of reporting worse QOL also increased. Specifically, with each additional reported condition, women had significantly higher odds of reporting good (OR = 1.22, 95% CI: 1.12, 1.32), fair (OR = 1.76, 95% CI: 1.58, 1.96), and poor/very poor QOL (OR = 2.31, 95% CI: 1.86, 2.88), as compared to very good QOL (Table 2). Unadjusted estimates of the relationship between the number of comorbid conditions and QOL are provided in S2 Table.

Table 2

Association between the number of comorbid conditions and quality of life among breast cancer survivors in the Transitions Study using multinomial logistic regression.

	OR (95% CI)a
	Good	Fair	Poor/Very Poor
	N = 1486 (44.1%)	N = 472 (14.0%)	N = 65 (1.9%)
Comorbid Conditions b	1.22 (1.12, 1.32)	1.76 (1.58, 1.96)	2.31 (1.86, 2.88)
Age	1.13 (1.03, 1.24)	1.04 (0.90, 1.19)	0.86 (0.63, 1.16)
Education	0.79 (0.70, 0.91)	0.62 (0.51, 0.76)	0.60 (0.38, 0.95)
Household Size	1.06 (0.96, 1.17)	1.10 (0.96, 1.26)	0.66 (0.43, 1.02)
Employment
Employed	REF	REF	REF
Unemployed/Paid Sick Leave	1.62 (1.22, 2.17)	4.33 (3.01, 6.22)	8.83 (3.80, 20.49)
Retired	0.87 (0.70, 1.08)	0.96 (0.69, 1.34)	1.49 (0.63, 3.57)
Marital Status
Single	REF	REF	REF
Married/Partnered	0.79 (0.56, 1.12)	0.38 (0.24, 0.59)	0.55 (0.21, 1.46)
Separated/Divorced/Widowed	0.84 (0.58, 1.22)	0.82 (0.51, 1.31)	0.54 (0.20, 1.47)
Physician in Charge of Follow-up	1.93 (1.19, 3.13)	2.09 (1.13, 3.88)	5.43 (2.15, 13.73)

Abbreviations: N = number, OR = odds ratio, REF = reference category.

aModels were adjusted for age, education, household size, employment status, marital status, and whether a physician was in charge of patient’s follow-up (coding details provided in S1 Table). The reference category was women reporting very good QOL (N = 1349, 40.0%).

Higher levels of education were consistently associated with a significantly lower odds of reporting worse QOL (OR = 0.79, 95% CI: 0.70, 0.91 for good, OR = 0.62, 95% CI: 0.51, 0.76 for fair, and OR = 0.60, 95% CI: 0.38, 0.95 for poor/very poor QOL, relative to very good QOL). Unemployed women, those on paid sick leave, and homemakers report worse QOL (OR = 1.62, 95% CI: 1.22, 2.17 for good, OR = 4.33, 95% CI: 3.01, 6.22 for fair, and OR = 8.83, 95% CI: 3.80, 20.49 for poor/very poor QOL, relative to very good QOL), relative to employed women. Being married or partnered was also associated with a lower odds of reporting worse QOL, although this association was only significant for reporting fair versus very good QOL (OR = 0.38, 95% CI: 0.24, 0.59). Lastly not having a physician in charge of overseeing follow-up care was associated with an increased odds of reporting worse QOL (OR = 1.93, 95% CI:1.19, 3.13 for good, OR = 2.09, 95% CI: 1.13, 3.88 for fair, and OR = 5.43, 95% CI: 2.15, 13.73 for poor/very poor QOL, relative to very good QOL) (Table 3). Unadjusted estimates of the relationship between the number of comorbid conditions and emotional health are provided in S2 Table.

Table 3

Association between the number of comorbid conditions and emotional health among breast cancer survivors in the Transitions Study using multinomial logistic regression.

	OR (95% CI)a
	Good	Fair	Poor/Very Poor
	N = 1668 (49.5%)	N = 615 (18.3%)	N = 124 (3.7%)
N Comorbid Conditions	1.17 (1.07, 1.28)	1.63 (1.46, 1.82)	2.17 (1.81, 2.60)
Age	0.97 (0.88, 1.08)	0.83 (0.72, 0.94)	0.72 (0.57, 0.91)
Education	0.79 (0.69, 0.91)	0.70 (0.58, 0.84)	0.62 (0.43, 0.88)
Household Size	0.95 (0.86, 1.06)	1.10 (0.97, 1.25)	0.80 (0.62, 1.03)
Employment
Employed	REF	REF	REF
Unemployed/Paid Sick Leave	1.54 (1.11, 2.15)	2.75 (1.89, 3.99)	8.01 (4.53, 14.17)
Retired	0.87 (0.69, 1.09)	0.91 (0.67, 1.24)	0.73 (0.39, 1.35)
Marital Status
Single	REF	REF	REF
Married/Partnered	1.03 (0.71, 1.50)	0.70 (0.45, 1.10)	0.55 (0.26, 1.17)
Separated/Divorced/Widowed	1.11 (0.75, 1.64)	0.99 (0.62, 1.61)	1.04 (0.48, 2.27)
Physician in Charge of Follow-up	2.29 (1.29, 4.07)	2.38 (1.22, 4.67)	6.66 (2.89, 15.35)

Abbreviations: N = number, OR = odds ratio, REF = reference category.

aModels were adjusted for age, education, household size, employment status, marital status, and whether a physician was in charge of patient’s follow-up (coding details provided in S1 Table). The reference category was women reporting very good emotional health (N = 965, 28.6%).

The majority of women reported either very good (29%) or good (50%) emotional health; with only 18% and 4% reporting fair and poor/very poor emotional health, respectively (Table 3). As the number of chronic conditions increased, the odds of reporting worse emotional health increased. Specifically, compared to women reporting very good emotional health, for each additional chronic condition, women had significantly higher odds of reporting good (OR = 1.17, 95% CI: 1.07, 1.28), fair (OR = 1.63, 95% CI: 1.46, 1.82) and poor/very poor (OR = 2.17, 95% CI: 1.81, 2.60) emotional health (Table 3).

Older women were less likely to report worse emotional health, although this association was only statistically significant for fair emotional health (OR = 0.83, 95% CI: 0.72, 0.94) and poor/very poor emotional health (OR = 0.72, 95% CI: 0.57, 0.91) relative to very good emotional health. As was seen for QOL, women with higher levels of education were less likely to report worse emotional health (OR = 0.79, 95% CI: 0.69, 0.91 for good, OR = 0.70, 95% CI: 0.58, 0.84 for fair, and OR = 0.62, 95% CI: 0.43, 0.88 for poor/very poor emotional health, relative to very good emotional health). Women who were unemployed, on paid sick leave, students, or homemakers reported significantly worse emotional health relative to those who were employed (OR = 1.54, 95% CI: 1.11, 2.15 for good; OR = 2.75, 95% CI: 1.89, 3.99 for fair; and OR = 8.01, 95% CI: 4.53, 14.17 for poor/very poor emotional health, relative to very good emotional health). Women who did not report having a physician in charge of overseeing their follow-up care reported significantly worse emotional health (OR = 2.29, 95% CI: 1.29, 4.07 for good; OR = 2.38, 95% CI: 1.22, 4.67 for fair; and OR = 6.66, 95% CI: 2.89, 15.35 for poor/very poor emotional health, relative to very good emotional health) (Table 3).

Discussion

Among breast cancer survivors in the Transitions Study, we found that with each additional reported chronic condition, participants were significantly more likely to report worse QOL and poorer emotional health. We also found that both overall QOL and emotional health were highest in women with higher educational attainment (more than a high school degree), those who had a physician in charge of their follow-up care, as well as those who were not unemployed or on paid sick leave.

The findings of our study may be explained by the additional physical and mental burden provoked by a breast cancer diagnosis among women already living with other chronic conditions. Prior research has also found that comorbid conditions can have a negative impact on health related QOL [28-31]. A recent prospective cohort study from the United States found that five years after breast cancer diagnosis, reporting one or more comorbid condition was associated with worse health related QOL scores [29]. Importantly, the study also concluded that poor health related QOL scores, were associated with a significantly increased hazard of all cause mortality [29]. Similarly, among breast cancer patients receiving chemotherapy, having a greater number of comorbid conditions has also been associated with poorer physical and role functioning, greater pain, worse sleep quality, and fatigue [30]. In a French cross-sectional study, having ≥2 comorbid conditions was associated with poorer QOL for the physical functioning and general health dimensions of the Short Form Health Survey (SF-12), but not the mental health dimension [31].

The impact of socioeconomic characteristics on QOL among breast cancer survivors is well documented [9, 32]. Prior research, and our current work have found that lower education levels and working as a homemaker or housewife are associated with worse QOL [33]. We also found that older women were less likely to report worse emotional health, consistent with prior work reporting poorer physical and psychosocial outcomes after breast cancer diagnosis among younger women [34, 35]. Further, women with breast cancer rely heavily on their physicians to provide information and support [36]. Positive communication with greater perceived self-efficacy in physician interactions is associated with better QOL [37]. Correspondingly, in our study, we found that not having a physician in charge of follow-up care was associated with worse QOL.

Chronic conditions can often worsen in severity and complexity over time, reducing individuals’ functional status and thereby reducing QOL and emotional health. The manifestation of various chronic conditions, and their impact on functioning can vary—for instance—among cancer survivors, conditions such as osteoarthritis are linked to reduced physical functioning, whereas chronic psychological conditions including depression are strongly linked to emotional function [38]. The prevalence of multimorbidity—the co-occurrence of two or more chronic conditions—increases with age, and is greater among those with lower household incomes, and lower educational attainment [39]. According to a Danish study of cancer patients more broadly, comorbidity explained more of the variance in physical and emotional function components of health related QOL than sociodemographic characteristics and cancer characteristics (e.g. years since diagnosis, tumour stage, and treatment) [38]. Given the increasing prevalence of chronic conditions, and acknowledging that poor physical and mental health related QOL is associated with increased all-cause mortality [29], planning breast cancer survivorship care with chronic conditions in mind remains highly important.

Having breast cancer also negatively impacts adherence to chronic disease medications, and fewer primary care provider visits among survivors are associated with higher odds of non-adherence [40]. This may exacerbate already poor QOL among breast cancer survivors with a high comorbidity burden. In Canada, where healthcare services are delivered at the provincial level, adherence to guidelines for quality follow-up care of breast cancer survivors varies widely between provinces [41]. This is especially true for the management of chronic conditions among breast cancer survivors, where British Columbia has much lower levels of compliance relative to Ontario and Nova Scotia [41]. Ensuring quality follow-up care that is compliant with Canadian guidelines can serve as a target for intervention in Canadian provinces where compliance is low e.g. British Columbia [41].

Strengths and limitations

This study has numerous strengths. First, the identification of study participants through provincial cancer agencies/registries, allowed for a source population of all individuals diagnosed with cancer within the province. Further, the Transitions Study survey development process included consultations with cancer survivors, clinicians and system leaders, as well as cognitive interviews with 15 cancer survivors to evaluate the questionnaire’s meaningfulness, clarity, understandability, and ease of completion, thereby limiting potential information bias [19]. The survey also underwent performance testing with 96 survivors, who were recruited to match the eligibility criteria, further reducing the potential for information bias [19]. In addition, the overall QOL measure included in the Transitions Study questionnaire is comparable the global QOL measure from the EORTC QLQ-C30, which has been validated for use in breast cancer patients [25-27]. We also attempted to capture the impact chronic conditions on emotional functioning, one of the core domains of the QLQ-C30 by including emotional health as a separate outcome in our analysis. Despite the use of self-report survey data, there is limited potential for differential recall bias as all participants in the sample are breast cancer survivors. In addition, while the data are cross-sectional, temporality can be established because the exposure (number of chronic conditions) is assessed at the time of breast cancer diagnosis—albeit retrospectively, and the outcomes (QOL and emotional health) are assessed after completion of treatment. Finally, participants were selected through probability sampling, with all eligible survivors surveyed in smaller provinces [19]. However since survey weights were not available, the findings may not be generalizable to all Canadian breast cancer survivors [16, 19].

Limitations of this study include the lack of data on several potentially important predictors of QOL (e.g., menopausal status, and cancer stage at diagnosis). While a 30% response rate was assumed by CPAC when designing the survey and the response rate was 33%, this does not preclude the potential for selection bias in the study sample. In addition, the lack of information on individuals who did not respond to the questionnaire hinders the assessment of the extent of selection bias.

Conclusion

Here we report that a higher burden of comorbidity was associated with worse QOL and poorer emotional health in a nationally representative sample of Canadians breast cancer survivors from the Transitions Study. These findings emphasize the importance of integrating information on chronic comorbid conditions into survivorship care to improve QOL and emotional outcomes of breast cancer survivors.

STROBE checklist for cross-sectional studies.

(DOCX)

Click here for additional data file.

Coding details of all variables included in Table 1, and corresponding questions, response options, and variable codes from the Canadian Partnership Against Cancer (CPAC) Transitions Study survey.

(DOCX)

Click here for additional data file.

Unadjusted estimates of the relationship between the number of chronic conditions at breast cancer diagnosis, and the study outcomes: (i) quality of life, and (ii) emotional health, among breast cancer survivors in the Transitions Study.

(DOCX)

Click here for additional data file.

23 Jun 2021

PONE-D-21-03223

The impact of chronic comorbidities at the time of breast cancer diagnosis on quality of life, and emotional health following treatment

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

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Reviewer #1: Dear Editor,

Thank you for the opportunity to review the manuscript entitled “The impact of chronic comorbidities at the time of breast cancer diagnosis on quality of life, and emotional health following treatment”. This is a well written paper with great importance. I only have a few suggestions.

1. It will be great to add the study setting to the topic so readers can easily know where the study was conducted

2. I will also urge the authors to follow the STROBE Checklist and attach it as a supplementary file.

3. Line 21…"Using cross-sectional survey…" I think the authors can move this to the methods section of the abstract

4. Line 35 reads introduction while in the abstract(line 12) you have background, please make them consistent

5. Line 97…”prior literature…”please provide references to support this

6. It will be prudent for the authors to create sub-sections for the strength and limitations as well as the conclusion

Reviewer #2: I enjoyed reading this manuscript which uses data on from 3,372 breast cancer survivors who participated in the Canadian Partnership Against Cancer (CPAC) Experiences of Cancer Patients in Transitions Survey to determine the impact of comorbidities on self-reported quality of life (QOL) and emotional health following a breast cancer diagnosis and treatment. The manuscript is well-written and when published will contribute significantly to the literature on chronic conditions. I have a few comments which I believe will make the manuscript even stronger if considered and incorporated by the authors

Abstract

• Line 21-22. I suggest the authors send “Using cross-sectional survey data from 3,372 breast cancer survivors who participated in the Transitions study,” back to the methods section of the abstract.

Background

• This section is okay and described in details.

Methods

• I suggest the authors adopt the STROBE checklist (https://www.strobe-statement.org/index.php?id=available-checklists) in reporting the study as this will ensure all possible missing pieces are fitted into the right places. This will make the paper even stronger in terms of value. The authors would have to then state at the beginning parts of the methods that they adopted STROBE in reporting their findings

• While the authors have tried to present the variables in the methods section, I suggest they provide a table which contains all the variables (both outcome and explanatory), how they were coded in the survey and the questions which were asked regarding each of them. Such a table will effectively take care of lines 142 – 150 for instance.

Results

• The percentage for Education in Table 1 is 100.1% instead of 100%. Authors should kindly check and effect any other such changes.

• A first look at the topic “… chronic comorbidities at the time of breast cancer diagnosis…” suggests that participants included in this study were individuals who had at least one chronic condition aside breast cancer at the time of diagnosis; thus, taking into consideration the question on line 149–150. I am, therefore, not clear regarding the inclusion of the attribute “O” under the variable “Number of chronic conditions” in Table 1.

Discussion

• The discussion could be strengthened even further. For instance, while I commend the authors for juxtaposing their findings to previous research, it is important to also discuss the possible reasons for the key findings made, especially from line 229–260.

• A few typos and grammatical issues identified are worth correcting through a further proofreading of the manuscript before resubmission.

• Considering the cross-sectional nature of the data used for the analysis, I suggest the include the associated limitations.

Reviewer #3: Dear Author

thanks for the good paper looking at the association of number of co-morbidities with QOL

Do you have data on patients who refused interview that you can compare with those who accepted to rule out bias (there was less than 30% Response)

Any reason you choose to present co-morbidities other than. variables with high OR such as 'unemployment, having a doctor and age?

was this study approved by ethics committee? If yes please provide list of members. if NO, please state if t was 'exempt,.

The table on income was it for those currently working or did it include pension/ retirement benefit?

**********

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Reviewer #1: Yes: Abdul-Aziz Seidu

Reviewer #2: No

Reviewer #3: Yes: Dr. Evans Amukoye

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29 Jul 2021

Dear Dr. David Teye Doku,

Academic Editor, PLOS ONE

Thank you for the opportunity to revise our manuscript, PONE‐D‐21‐03223, entitled, “The impact of chronic comorbidities at the time of breast cancer diagnosis on quality of life, and emotional health following treatment.” The Reviewers provided a thoughtful review and we believe the manuscript is improved after addressing their comments. Please see below for a point-by-point response to each comment/question. All edits to the manuscript are indicated using tracked changes and a clean version of the manuscript is also included. All line numbers referenced in the response to reviewers below refer to the clean version.

I would like to thank you for considering our manuscript.

Sincerely,

Jennifer Brooks

Assistant Professor

Dalla Lana School of Public Health, University of Toronto

Response to Journal Requirements

JR1. 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 and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response: Thank you, we have ensured that our manuscript meets the style requirements.

JR2. 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.

Response: Thank you, we have double checked our reference list. Our manuscript does not include any retracted papers. Changes to our references list include the addition of the following four references:

4. DuMontier C, Clough-Gorr KM, Silliman RA, Stuck AE, Moser A. Health-Related Quality of Life in a Predictive Model for Mortality in Older Breast Cancer Survivors. Journal of the American Geriatrics Society. 2018;66(6):1115-22.

21. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting Observational Studies. PLOS Medicine. 2007;4(10):e296.

22. Montazeri A, Vahdaninia M, Harirchi I, Ebrahimi M, Khaleghi F, Jarvandi S. Quality of life in patients with breast cancer before and after diagnosis: an eighteen months follow-up study. BMC cancer. 2008;8(1):330.

23. Mokhatri-Hesari P, Montazeri A. Health-related quality of life in breast cancer patients: review of reviews from 2008 to 2018. Health and quality of life outcomes. 2020;18(1):338.

JR3. In your Methods section, please provide additional information about the participant recruitment method and the demographic details of your participants. Please ensure you have provided sufficient details to replicate the analyses such as a) the recruitment date range (month and year), b) a description of how participants were recruited.

Response: The data used in our study come from the Experiences of Cancer Patients in Transitions Study (Transitions Study) and were previously collected by the Canadian Partnership Against Cancer (CPAC). We were not involved in the recruitment of participants in any way, and only had access to data that is available in the public domain. We have also referenced two papers published by CPAC-affiliated scientists, (references 19 and 20) that provide more in-depth information about recruitment. We were not able to provide the month of recruitment as that information was not available to us, however, we have provided the year of recruitment, and the range of weeks (8-19) it took to recruit participants in the 10 Canadian provinces. Additional information on participant recruitment is summarized in our manuscript (lines 78-91). Demographic characteristics of the study population are found in Table 1.

JR4. In the ethics statement in the manuscript Methods and the online submission form, please state whether you had access to any identifying information associated with the data, or if they were fully anonymised before access.

In addition, please state whether you were involved in any aspect of the original study including study design, data collection, analysis or manuscript preparation, or whether the data were exclusively obtained from a publicly available source

Response: Anonymized data were used in this study. We have added to the Methods section that the data used in this study are in the public domain and freely available through the CPAC website. The authors were not involved in any aspect of the original study and did not have access to any identifying information associated with the data (lines 90-92). The authors exclusively obtained the data from the CPAC website.

Response to Reviewer Comments

Reviewer 1

R1.1 It will be great to add the study setting to the topic so readers can easily know where the study was conducted

Response 1.1 Thank you for this suggestion, we have added “in Canada” to the title.

R1.2 I will also urge the authors to follow the STROBE Checklist and attach it as a supplementary file.

Response 1.2 Thank you for this suggestion, we have completed a STROBE checklist and attached it as a supplementary file, and added this to the Methods section (line 93-94) As required in the STROBE guidelines, we have also provided unadjusted estimates of our results, available in S2 Table for both outcomes (quality of life and emotional health).

R1.3 Line 21…"Using cross-sectional survey…" I think the authors can move this to the methods section of the abstract

Response 1.3 Thank you, we have removed the sentence from the Results section of the abstract and identified the survey as cross-sectional in the Methods section of the abstract.

R1.4 Line 35 reads introduction while in the abstract (line 12) you have background, please make them consistent

Response 1.4 Thank you for pointing that out, we have changed “Background” to “Introduction” in the Abstract.

R1.5 Line 97… “prior literature…”please provide references to support this

Response 1.5 Thank you, we have added references to support our point that the prior literature largely uses health related quality of life (line 112).

R1.6 It will be prudent for the authors to create sub-sections for the strength and limitations as well as the conclusion

Response 1.6 We have now created a Strengths and Limitations sub-section and a Conclusion sub-section to the Discussion.

Reviewer #2:

Abstract

R2.1 Line 21-22. I suggest the authors send “Using cross-sectional survey data from 3,372 breast cancer survivors who participated in the Transitions study,” back to the methods section of the abstract.

Response 2.1 Thank you, we have removed the sentence from the Results section of the abstract and identified the survey as cross-sectional in the Methods section of the abstract.

Background

R2.2 This section is okay and described in details.

Response 2.2 Thank you.

Methods

R2.3 I suggest the authors adopt the STROBE checklist (https://www.strobe-statement.org/index.php?id=available-checklists) in reporting the study as this will ensure all possible missing pieces are fitted into the right places. This will make the paper even stronger in terms of value. The authors would have to then state at the beginning parts of the methods that they adopted STROBE in reporting their findings

Response 2.3 Thank you for this suggestion. We have now completed the STROBE checklist and included it as a supplementary file. This information is included in the Methods section (line 93-94). As required in the STROBE guidelines, we have also provided unadjusted estimates of our results, available in the S2 Table for both outcomes (quality of life and emotional health).

R2.4 While the authors have tried to present the variables in the methods section, I suggest they provide a table which contains all the variables (both outcome and explanatory), how they were coded in the survey and the questions which were asked regarding each of them. Such a table will effectively take care of lines 142 – 150 for instance.

Response 2.4 Thank you for this suggestion. We have included a table describing all the variables (exposure, outcome, and covariates) as a supplementary table (S1 Table). We have noted this in the Methods section (Statistical Analysis subsection line 136) as well as in the footnotes to Table 2 and 3 (lines 167 and 189, respectively).

Results

R2.5 The percentage for Education in Table 1 is 100.1% instead of 100%. Authors should kindly check and effect any other such changes.

Response 2.5 The percentages may not always add up to 100% due to rounding. We have added a footnote to clarify this, stating “Percentages may not add up to 100% in some cases due to rounding.”(line 153).

R2.6 A first look at the topic “… chronic comorbidities at the time of breast cancer diagnosis…” suggests that participants included in this study were individuals who had at least one chronic condition aside breast cancer at the time of diagnosis; thus, taking into consideration the question on line 149–150. I am, therefore, not clear regarding the inclusion of the attribute “O” under the variable “Number of chronic conditions” in Table 1.

Response 2.6 We thank the reviewer for noting this. We report in the abstract and in the Results section that 57% of the participants report at least one chronic condition, which implies that 43% of the population has 0 chronic conditions. On lines 103-106 also provide details as to the definition of the “number of chronic conditions” variable. We did not have any inclusion criteria based on number of comorbidities, but rather are investigating the impact of having comorbidities on QOL and emotional health. Individuals without comorbidities are used as a comparison group.

Discussion

R2.7 The discussion could be strengthened even further. For instance, while I commend the authors for juxtaposing their findings to previous research, it is important to also discuss the possible reasons for the key findings made, especially from line 229–260.

Response 2.7 Thank you this suggestion. We have discussed possible explanations for our findings on lines 220-221.

R2.8 A few typos and grammatical issues identified are worth correcting through a further proofreading of the manuscript before resubmission.

Response 2.8 Thank you, we have proofread the manuscript and hope to have corrected all typographical and grammatical errors.

R2.9 Considering the cross-sectional nature of the data used for the analysis, I suggest the include the associated limitations.

Response 2.9 Thank you for noting this. We have addressed the use of cross-sectional data in our Strengths and Limitations section (lines 279-282). We do not believe that the use of cross-sectional data in this case is a limitation because temporality can be established because the exposure (number of chronic conditions) is assessed at the time of breast cancer diagnosis—albeit retrospectively, and the outcomes (QOL and emotional health) are assessed after completion of treatment.

Reviewer 3:

R3.1 Do you have data on patients who refused interview that you can compare with those who accepted to rule out bias (there was less than 30% Response)

Response 3.1 Thank you for this question. We do not have information on individuals who did not complete the questionnaire. The survey was conducted by the Canadian Partnership Against Cancer (CPAC), and we have provided a reference to their published paper (Shakeel et al 2020), where they state: “A total of 40 790 survey packages were mailed across the 10 provinces and 13 319 responses were received (response rate = 33%); 12 929 surveys were completed by survivors aged 30 years or older.” A 30% response rate was assumed by CPAC when designing the survey. This does not preclude the potential for selection bias in the study sample and this has now been noted as a potential limitation (line 287-291)

R3.2 Any reason you choose to present co-morbidities other than. variables with high OR such as 'unemployment, having a doctor and age?

Response 3.2 Thank you for this question. The purpose of our study was to determine the relationship between the burden of comorbidity and quality of life (QOL) and emotional health. Since our primary exposure was the burden of comorbidity (as captured by the variable “number of chronic conditions”) we presented the corresponding results. The other variables included in the model (age, education, household size, employment status, marital status, and having a physician in charge of follow up) have previously been established as risk factors for poor QOL and poor emotional health in the literature and have been included in our analysis as potential confounders.

R3.3 was this study approved by ethics committee? If yes please provide list of members. if NO, please state if t was 'exempt,.

Response 3.3 This study was exempt from Research Ethics Board review as it was conducted with publicly available anonymized data with no personally identifiable information. We have included a statement to this effect (lines 94-95).

R3.4 The table on income was it for those currently working or did it include pension/ retirement benefit?

Response 3.4 The income distribution in Table 1 includes the entire sample regardless of employment status (employed, unemployed, homemaker, student, on paid sick leave, retired). This is now indicated in footnote ‘c’ for S1 Table which provides details on the coding of all variables. Please also note that we did not include the income variable in our models (also indicated in the same footnote).

Submitted filename: Response to Reviewers.pdf

Click here for additional data file.

10 Aug 2021

The impact of chronic comorbidities at the time of breast cancer diagnosis on quality of life, and emotional health following treatment in Canada

PONE-D-21-03223R1

Dear Dr. Brooks,

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.

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Kind regards,

David Teye Doku

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

19 Aug 2021

PONE-D-21-03223R1

The impact of chronic comorbidities at the time of breast cancer diagnosis on quality of life, and emotional health following treatment in Canada

Dear Dr. Brooks:

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.

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Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

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on behalf of

Dr. David Teye Doku

Academic Editor

PLOS ONE