A Prospective Study of Sleep Quality in Women Undergoing Chemotherapy for Breast, Ovarian, and Endometrial Cancer

doi:10.21203/rs.3.rs-3929849/v1

Download PDF

Research Article

A Prospective Study of Sleep Quality in Women Undergoing Chemotherapy for Breast, Ovarian, and Endometrial Cancer

https://doi.org/10.21203/rs.3.rs-3929849/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Purpose To describe changes and assess associations in sleep quality and quality of life (QOL) among chemotherapy naïve women undergoing treatment for breast, ovarian, or endometrial cancer Methods A prospective cohort study was performed in a Women’s Oncology Program. Sleep quality was measured with the Pittsburgh Sleep Quality Index (PSQI) and QOL using the Functional Assessment of Cancer Therapy (FACT) prior to-, halfway through-, at completion of-, and 6 months after chemotherapy. Patients with ovarian and endometrial cancers were combined into one group (GynCa) for analysis. The PSQI and FACT scores were analyzed using multivariable linear and logistic regression. Results Of the 102 eligible patients, 97 participants enrolled: breast (n=47), ovarian (n=27), and endometrial (n=23). Prior to starting chemotherapy, 59% of women reported poor sleep quality. By mid-treatment, both groups experienced worsening sleep quality: breast (p=.05) and GynCa (p=.04), and QOL: breast (p=0.0001) and GynCa (p=0.02). Changes in sleep quality did not persist at treatment completion. A significant QOL improvement was reported among GynCa patients compared to the breast cohort at 6-months post-treatment (p=0.047). Poorer sleep quality was associated with lower QOL at most study time points. Conclusions The majority of chemotherapy naïve women reported poor sleep at baseline. By treatment completion, average PSQI scores continued to show clinically significant sleep disturbances. Poor sleep quality is associated with lower QOL, a prognostic indicator for survival. Future work should examine whether disturbed sleep during chemotherapy worsens treatment outcomes. Poor sleep may be a novel therapeutic target in this population

Sleep is a vital human function and sleeping less than five hours per night increases the risk of death from all causes by about 15 percent [1]. Sleep disorders are so pervasive that the CDC considers them a public health epidemic [2]. Although sleep disturbance has been acknowledged as a common problem among cancer patients, estimates of prevalence range widely from 23 to 61%.[3–9]. Particularly concerning are observations that poor sleep quality may be associated with discontinuation of treatment, increased morbidity, and decreased quality of life among women with cancer [10–12]. One metanalysis showed a dose response relationship between insufficient and excessive sleep and cancer mortality [13].

Much of the literature on sleep in women’s cancer has centered around breast cancer (BC). BC patients report sleep disturbances during and up to five years after chemotherapy ^[14,15]. Sleep disturbance among women with ovarian cancer (OC) and endometrial cancer (EC) is not as well understood. One study of EC patients found that most survivors were affected by poor sleep quality during their treatment, particularly those who received combined chemotherapy and radiation [16]. Another study in OC patients reported a high proportion of women with sleep disturbances before surgery and up to one year after surgical treatment. Overall, the limited available studies suggest that sleep disturbances in this patient population are associated with decreased quality of life, which in turn is associated with worse prognosis for survival [15–17]. There is a paucity of data evaluating sleep quality during chemotherapy.

The purpose of this study was to assess sleep quality during chemotherapy for women with breast, ovarian, and endometrial cancer. Our secondary aims were two-fold: (1) to assess quality of life throughout chemotherapy and (2) to compare the subjective sleep quality during chemotherapy between BC patients and OC/EC patients.

Chemotherapy naïve women diagnosed with breast, ovarian, or endometrial cancer scheduled to begin cytotoxic treatment in the Women’s Oncology Program at our academic tertiary care center were identified by a clinician or a nurse navigator. Participants were English-speaking,18 years or older and able to provide consent. Approval was obtained from the Institutional Review Board. This study was conducted in accordance with the principles of the Declaration of Helsinki, and all patients provided written informed consent prior to enrollment.

Participants completed two validated questionnaires: the Pittsburgh Sleep Quality Index (PSQI) and the Functional Assessment of Cancer Therapy (FACT) at four time points: prior to starting chemotherapy, halfway through chemotherapy, chemotherapy completion, and 6-months post completion. Questionnaires were completed using an iPad either in the outpatient clinic or the infusion center. We also collected patient characteristics including age, post-menopausal status (defined as self-report of no menstrual cycles in the 12 months preceding diagnosis), self-reported race/ethnicity, insurance status, cancer type, stage, surgical history, residual disease prior to starting chemotherapy, body mass index, medical comorbidities, medications, self-reported alcohol, caffeine, and nicotine use, and prior history of sleep related problems.

Measures

The PSQI is a seven domain (19-item) self-rated questionnaire that evaluates usual sleep habits during the last month. The seven domain scores include: subjective sleep quality, sleep latency, sleep duration, sleep efficiency, daytime dysfunction, sleep disturbance, and use of sleep aid medications. These domain scores are combined to provide a global sleep quality index score where good sleep quality and poor sleep quality are defined as PSQI score ≤ 5 and > 5, respectively [18]. PSQI scores > 5 have a sensitivity of 89.6% and specificity of 86.5% for detecting clinically significant insomnia. In our sample, the PSQI showed good internal reliability with a Cronbach’s alpha of 0.78.

The FACT disease specific questionnaires: FACT-O, FACT-B, and FACT-En, used to measure health related quality of life in cancer patients, were administered to women with ovarian, breast and endometrial cancer, respectively. All questionnaires are comprised of the FACT-G and include a disease specific subscale. The FACT-G is a sum of the Physical, Social, Emotional, and Functional Well-Being (FWB) subscales scored from 0-108 with a higher score indicative of better QOL. A change in baseline of 5 or more points has been associated with a clinically relevant improvement or decline in health status [19].

Statistical Analysis

Our a priori sample size calculation was based on PSQI scores from prior research in similar patients [17]. A total of 98 patients were required to detect a 1-point or greater change in mean PSQI score at 5% significance and 80% power by paired T-test. Additionally, we determined a total of 31 patients were required per group to detect a 2.5 point or greater change in mean PSQI score at 5% significance, 80% power, and SD = 3.5 by T-test for between group differences. OC and EC patients were considered one group (GynCa).

We compared baseline characteristics between cancer groups by Fisher’s exact for categorical variables and T-test or Wilcoxon rank sum test. PSQI to and FACT-G scores were examined using multivariable linear regression with generalized estimating equations (GEEs). PSQI score was also examined as a dichotomous outcome (score ≤ 5 vs. > 5) by logistic regression with GEEs, where PSQI > 5 indicates poor sleep. Baseline demographic and clinical covariates associated with outcomes of p < 0.1 were included in the adjusted models. To avoid multicollinearity, this analysis was performed without the FACT Functional Well-Being item, “I am sleeping well”, as part of the FACT-G score. All available outcome data points were included in the models, and bias due to missing data was handled by regression adjustment. Data analysis was performed with SAS version 9.4 (SAS Institute, Cary, NC).

Participation and Protocol Adherence

We identified 102 eligible patients and 99 enrolled: 49 with BC, 27 with OC, and 23 with EC. The three women who declined to participate reported that they were not interested in research studies. After consent was signed, we discovered that 2 BC patients had previously received chemotherapy and were ineligible; thus 97 patients were analyzed. (Fig. 1)

PSQI questionnaire completion rates were 95% at baseline, 84% at mid-treatment, 82% at the end of treatment, and 85% at 6 months post treatment. FACT-G completion rates were 96% at baseline, 91% at mid-treatment, 86% at the end of treatment, and 90% at 6 months post treatment for the FACT.

Demographics and Clinical Characteristics

BC patients were younger than GynCa patients: mean age: 52 vs. 62 years (p < .001), and more likely to identify as Hispanic (12.8% vs. 0%, p = 0.01). There were no differences in insurance, marriage status, or education. English was the primary language for all participants. (Table 1)

Table 1

Demographics
	All patients (n = 97)	GynCa (n = 50)	Breast Cancer (n = 47)	P-value
Age (y)
Mean (SD)	57.4 (12.2)	62.1 (10.5)	52.3 (11.9)	< 0.001
Range	27, 84	31, 84	27, 74
Race, n (%)
Black/African American	4 (4.1)	2 (4.0)	2 (4.3)	0.06
White/Caucasian	82 (84.5)	46 (92.0)	36 (76.6)
Other/Multiracial	11 (11.3)	2 (4.0)	9 (19.1)
Ethnicity, n (%)	(n = 96)	(n = 49)
Hispanic	6 (6.3)	0 (0.0)	6 (12.8)	0.01
Not Hispanic	90 (93.8)	49 (100.0)	41 (87.2)
Insurance, n (%)	(n = 94)	(n = 48)	(n = 46)
Private	62 (66.0)	29 (60.4)	33 (71.7)	0.33
Public	31 (33.0)	18 (37.5)	13 (28.3)
Uninsured/Self-pay	1 (1.1)	1 (2.1)	0 (0.0)
Marital status, n (%)
Married/Living with partner	52 (53.6)	23 (46.0)	29 (61.7)	0.14
Single	14 (14.4)	8 (16.0)	6 (12.8)
Divorced/Separated	17 (17.5)	8 (16.0)	9 (19.1)
Widowed	14 (14.4)	11 (22.0)	3 (6.4)
Education, n (%)	(n = 94)	(n = 48)	(n = 46)
High school equivalent or less	26 (27.7)	12 (25.0)	14 (30.4)	0.21
More than high school	28 (29.8)	11 (22.9)	17 (37.0)
Bachelor's degree	26 (27.7)	15 (31.3)	11 (23.9)
Graduate degree	14 (14.9)	10 (20.8)	4 (8.7)

Number with non-missing data is included in parentheses when less than the total.

GynCa, ovarian or endometrial cancer

Over 90% of BC patients had Stage I or II invasive ductal carcinoma (IDC). 70% of OC patients were Stage III or IV at diagnosis, and approximately half received neoadjuvant chemotherapy. Adjuvant chemotherapy was administered more frequently in patients with BC (59%) and EC (83%). Similar rates of depression, anxiety, and obstructive sleep apnea were reported between groups. Hypertension was the most frequently reported comorbidity and was more common in GynCa patients (48.0% vs. 23.4%, p = 0.02). Medication and caffeine use was similar for both groups, while more BC patients reported alcohol use (44.7% vs. 24.0%, p = 0.04). (Table 2)

Table 2

Clinical Characteristics at Baseline
	All patients (n = 97)	GynCa (n = 50)	Breast Cancer (n = 47)	P-value
Clinical cancer stage, n (%)
I	35 (36.1)	16 (32.0)	19 (40.4)	< 0.0001
II	30 (30.9)	5 (10.0)	25 (53.2)
III	23 (23.7)	20 (40.0)	3 (6.4)
IV	9 (9.3)	9 (18.0)	0 (0.0)
Recurrent cancer, n (%)	4 (4.1)	2 (4.0)	2 (4.3)	1.0
Planned chemotherapy, n (%)
Neoadjuvant	39 (40.2)	16 (32.0)	23 (48.9)	0.10
Adjuvant	58 (59.8)	34 (68.0)	24 (51.1)
BMI (kg/m²)	(n = 94)	(n = 47)
Mean (SD)	30.9 (8.3)	31.6 (8.6)	30.2 (8.0)	0.43
Post-menopausal, n (%)	35 (36.1)	25 (50.0)	10 (21.3)	0.006
Performance status, n (%)	(n = 88)	(n = 45)	(n = 43)
0	74 (84.1)	35 (77.8)	39 (90.7)	0.14
1	12 (13.6)	9 (20.0)	3 (7.0)
2	2 (2.3)	1 (2.2)	1 (2.3)
Comorbidities, n (%)
Depression	19 (19.6)	11 (22.0)	8 (17.0)	0.61
Anxiety	18 (18.6)	8 (16.0)	10 (21.3)	0.60
Diabetes	14 (14.4)	8 (16.0)	6 (12.8)	0.78
Hypertension	35 (36.1)	24 (48.0)	11 (23.4)	0.02
Chronic obstructive pulmonary disease	1 (1.0)	1 (2.0)	0 (0.0)	1.0
Obstructive sleep apnea	3 (3.1)	2 (4.0)	1 (2.1)	1.0
Medications, n (%)
Benzodiazepines	29 (29.9)	13 (26.0)	16 (34.0)	0.51
Sleep agents	10 (10.3)	4 (8.0)	6 (12.8)	0.52
Antidepressants	23 (23.7)	12 (24.0)	11 (23.4)	1.0
Opioids	10 (10.3)	6 (12.0)	4 (8.5)	0.74
Any caffeine consumption, n (%)	71 (73.2)	36 (72.0)	35 (74.5)	0.82
Any alcohol consumption, n (%)	33 (34.0)	12 (24.0)	21 (44.7)	0.04

Number with non-missing data is included in parentheses when less than the total.

GynCa, ovarian or endometrial cancer; BMI, body mass index.

Sleep

Fifty-nine percent of patients in our cohort (64% in the BC group and 53% in the GynCa group; p = 0.30) reported poor sleep quality at baseline. At mid-treatment, the proportion of patients reporting poor sleep quality in the entire cohort increased significantly to 73% (p = 0.006) but did not differ significantly between groups (p = 0.28). (Fig. 2A) Mean PSQI scores at subsequent visits were not different from baseline values for either group, and no significant between-group differences in score changes from baseline were observed. Most patients continued to report clinically significant sleep disturbance at the end of chemotherapy, and 6-months after treatment. (Fig. 2B)

Figure 2. Subjective Sleep Quality and Quality of Life over time by malignancy

A) Subjective Sleep Quality by PSQI

B) Percent of participants with PSQI > 5

PSQI, Pittsburgh Sleep Quality Index (higher = worse quality)

Gyn, Gynecologic (endometrial or ovarian cancer)

Adjusting for baseline age, sleep agent use, and opioid use, mean PSQI score increased from baseline to mid-treatment by 1.3 points (p = 0.04) in GynCa patients and 1.2 points (p = 0.05) in BC patients. (supplementary)

Quality of Life

Baseline FACT-G scores were 81.5 and 82.1 for the GynCa and BC groups, respectively. While the FACT-G does not provide reference values for scores, a study looking at over 5000 patients with a cancer diagnosis found that the mean FACT-G in this population was 79.3 [20]. (Fig. 2C) By six months post-treatment, mean FACT-G was 6 points higher than at baseline (p = 0.047) in the GynCa group, but the BC group score was 2 points lower that at baseline resulting in a

significant between group difference, (p = 0.03). Adjusting for baseline age, opioid use, and history of anxiety or depression, mean FACT-G scores decreased significantly by over 5-points in each group by mid-treatment. (supplementary)

C) Quality of Life by FACT-G

FACT-G, Functional Assessment of Cancer Therapy (higher score = better quality)

Gyn, Gynecologic (endometrial or ovarian cancer)

Associations between Sleep and QOL

Poor sleep quality was inversely and significantly associated with QOL. (Fig. 3) On average, each one-point increase in PSQI score, indicative of worsening sleep quality, was associated with a 1.6-to-3.1-point lower QOL score. GynCa and BC patients had similar associations between sleep quality and QOL at baseline and 6 months post treatment but had different trajectories between treatment initiation and the end of treatment.

PSQI, Pittsburgh Sleep Quality Index (higher = worse quality); FACT-G, Functional Assessment of Cancer Therapy (higher score = better quality); GynCa, Gynecologic cancer (endometrial or ovarian cancer)

FACT-G item pertaining to sleep quality was omitted from the score

In this prospective study evaluating sleep quality in chemotherapy naïve women undergoing treatment for breast, ovarian, or endometrial cancer, the majority of our sample reported poor sleep quality after diagnosis and prior to initiating treatment. Moreover, sleep disturbance rates increased after starting chemotherapy and remained elevated up to 6 months post-treatment.

The rates of sleep disturbance in our study are comparable to prior work. Westin et al. reported sleep disturbance in 54.9% of gynecologic cancer survivors [21].. While Clevenger et al found that 70% of women with OC had disturbed global sleep (PSQI > 5) with 24% severe enough to be considered clinically impaired (PSQI ≥ 10) at baseline [17]. Another study found that 25% of patients with EC experienced poor sleep quality at diagnosis, however after receiving systemic treatment, 86% reported poor sleep quality at treatment completion [16]. Sleep disturbances have also been described among BC patients with one study showing poor sleep quality in > 60% of patients at baseline and during chemotherapy while 38% of 5-year BC survivors reported experiencing sleep problems [12, 20]. Our study is novel in that we examined associations between disturbed sleep and overall quality of life, compared sleep disturbances between women with different types of malignancies, and assessed sleep quality at multiple points across the course of chemotherapy.

The reasons for sleep disturbance in gynecologic malignancies remain poorly understood. Cancer patients repeatedly endure multiple overlapping and interacting physical and emotional events that likely play a mechanistic role but are difficult to disentangle. The comparison of BC and GynCa patients, in this study, may provide insight into a contributing factor in sleep disturbance. The BC patients in our study were significantly younger than their GynCa counterparts and therefore, more likely to be pre- or peri-menopausal at the time of diagnosis. Menopausal symptoms, such as hot flashes, have been found to be associated with less efficient and more disrupted sleep [22, 23]. While menopausal status was ascertained in this study, menopausal symptoms were not. This could, in part, explain why a higher percentage of patients in the BC group reported poor sleep quality both at baseline (BC: 64%, GynCa: 53%) and 6 months post-treatment (BC: 63%, GynCa: 46%).

Our quality-of-life results findings provide another example of the complexity of pinpointing the factors that underlie sleep disturbance. At baseline FACT-G scores of both GynCa and BC participants were comparable to reference values for adult cancer patients [23]. At 6-months post treatment, however, we saw improved FACT-G scores compared to baseline among our GynCa patients but not among our BC patients. We speculate that there could be an interaction between improvement in symptomatic disease burden- seen frequently in advanced stage OC and EC patients at initial diagnosis- and worsening vasomotor symptoms in the BC group over the course of treatment. Future research examining the mechanisms contributing to poor sleep among women with gynecologic cancers would benefit from more fine-grained assessments of known contributing factors, i.e., longitudinal collection of contemporaneous menopausal symptoms across chemotherapy.

Strengths of our study are the high enrollment and retention rates − 97% of women approached agreed to participate in the study, 95% were eligible, and 97% of those who enrolled participated at all 4 time points and the overall questionnaire completion rate was 80%– supporting the feasibility and acceptability of this study design. Limitations of this study include the heterogeneity of cancer diagnoses and the homogeneity of the study sample with respect to demographic factors that are considered social determinants of health. Future work examining sleep in women with gynecologic cancers should include a more diverse sample, as racial and ethnic health disparities have been described both in cancer and in sleep health [24].

Although poor sleep quality was associated with lower QOL at most study time points in both the GynCa and BC patients, it is important to note that we cannot determine a causal relationship. What is known from the literature is that patients with worse health related QOL have poorer survival across a variety of malignancies [25–27]. The assessment and identification of strategies to deal with sleep disturbance are of paramount importance since poor sleep quality represents a potentially modifiable factor that, could be targeted to improve QOL and subsequently impact cancer prognosis in a group of malignancies that almost exclusively affect women. An interesting finding from this study is the baseline to mid-treatment period where both sleep quality and QOL worsened significantly in both groups. This has not been reported in other studies and represents a time point of interest.

This is one of the few studies to examine subjective sleep quality during chemotherapy longitudinally among women with OC and EC. It is also one of the few to compare BC and GynCa. The design is replicable and future studies should aim to answer this question in a larger, more heterogeneous study population. The PSQI is easily administered and has a sensitivity of 90% and a specificity of 87% making it an appropriate tool for evaluation [18]. Future studies using tools like actigraphy, sleep diaries, and polysomnography would provide objective sleep data to complement the PSQI while measurement of hormonal biomarkers (e.g., FSH, LH, cortisol) could help specify possible mechanisms through which sleep quality is negatively impacted.

Conflicts of Interest:

The authors have no relevant financial or non-financial interests to disclose.

Funding:

No funding was received to assist with the preparation of this manuscript.

Author Contribution

E.C., K.S. and K.R. wrote the main manuscript textE.C. and C.R. prepared figuresE.C., C.L., and C.R. participated in data entry and analysisAll authors reviewed the manuscript

Hublin C, Partinen M, Koskenvuo M, Kaprio J. Sleep and mortality: a population-based 22-year follow-up study. Sleep. 2007;30(10):1245–53. doi: 10.1093/sleep/30.10.1245. PMID: 17969458; PMCID: PMC2266277.
Centers for Disease Control and Prevention. Sleep and Sleep Disorders. Updated December 2022. https://www.cdc.gov/sleep/about_us.html. Accessed April 2023.
Miller AH, Ancoli-Israel S, Bower JE, et al. Neuroendocrine-immune mechanisms of behavioral comorbidities in patients with cancer. J Clin Oncol 2008;26:971–982. oi: 10.1200/JCO.2007.10.7805. PMID: 18281672; PMCID: PMC2770012.
Savard J, Morin CM. Insomnia in the context of cancer: a review of a neglected problem. J Clin Oncol 2001;19:895–908. doi: 10.1200/JCO.2001.19.3.895. PMID: 11157043.
Davidson JR, MacLean AW, Brundage MD, et al. Sleep disturbance in cancer patients. Soc Sci Med 2002;54:1309–1321. doi: 10.1016/s0277-9536(01)00043-0. PMID: 12058848.
Fiorentino L, Ancoli-Israel S. Insomnia and its treatment in women with breast cancer. Sleep Med Rev 2006;10:419–429. doi: 10.1016/j.smrv.2006.03.005. Epub 2006 Sep 11. PMID: 16963293; PMCID: PMC2757010.
Mao JJ, Armstrong K, Bowman MA, et al. Symptom burden among cancer survivors: impact of age and comorbidity. J Am Board Fam Med 2007;20:434–443. doi: 10.3122/jabfm.2007.05.060225. PMID: 17823460.
Savard J, Villa J, Ivers H, et al. Prevalence, Natural Course, and Risk Factors of Insomnia Comorbid With Cancer Over a 2-Month Period. J Clin Oncol 2009; 27(31):5233–5239. doi: 10.1200/JCO.2008.21.6333. Epub 2009 Sep 8. PMID: 19738124.
Oxana G, Palesh J, Roscoe K, et al. Prevalence, Demographics, and Psychological Associations of Sleep Disruption in Patients with Cancer: University of Rochester Cancer Center – Community Clinical Oncology Program. J Clin Oncol 2010;8(2):292–298. doi: 10.1200/JCO.2009.22.5011. Epub 2009 Nov 23. PMID: 19933917; PMCID: PMC2815717.
Otte JL, Carpenter JS, Manchanda S, et al. Systematic review of sleep disorders in cancer patients: can the prevalence of sleep disorders be ascertained? Cancer Med 2015; Feb; 4(2): 183–200. doi: 10.1002/cam4.356. Epub 2014 Nov 30. PMID: 25449319; PMCID: PMC4329003.
Kidwell, K. M., Harte, S. E., Hayes DF, et al. Patient-reported symptoms and discontinuation of adjuvant aromatase inhibitor therapy. Cancer 2014;120: 2403–2411. doi: 10.1002/cncr.28756. Epub 2014 May 6. PMID: 24802413; PMCID: PMC4126845.
Liu L, Rissling M, Natarajan L, et al. The Longitudinal Relationship between Fatigue and Sleep in Breast Cancer Patients Undergoing Chemotherapy. Sleep 2012; Feb 1; 35(2): 237–245. doi: 10.5665/sleep.1630. PMID: 22294814; PMCID: PMC3250363.
Li Y, Cai S, Ling Y, et al. Association between total sleep time and all cancer mortality: non-linear dose-response meta-analysis of cohort studies. Sleep Med 2019; Aug;60:211–218. doi: 10.1016/j.sleep.2019.03.026. Epub 2019 Apr 24. PMID: 31182327.
Lindley C, Vasa S, et al. Quality of life and preferences for treatment following systemic adjuvant therapy for early-stage breast cancer. J Clin Oncol. 1998; Apr;16(4):1380-7. doi: 10.1200/JCO.1998.16.4.1380. PMID: 9552041.
Sandadi S, Frasure HE, et al. The effect of sleep disturbance on quality of life in women with ovarian cancer. Gynecol Oncol. 2011; Nov; 123(2):351-5. doi: 10.1016/j.ygyno.2011.07.028. PMID: 21855973.
Tuyan İlhan T, Uçar MG. Sleep quality of endometrial cancer survivors and the effect of treatments. Turk J Obstet Gynecol. 2017; Dec;14(4):243–248. doi: 10.4274/tjod.59265. Epub 2017 Dec 30. PMID: 29379668; PMCID: PMC5780569.
Clevenger L, Schrepf A, et al. Sleep disturbance, distress, and quality of life in ovarian cancer patients during the first year after diagnosis. Cancer. 2013; Sep 1; 119(17):3234–41. doi: 10.1002/cncr.28188. Epub 2013 Jun 24. PMID: 23797955; PMCID: PMC3775963.
Buysse DJ, Reynolds CF, et al. The Pittsburgh Sleep Quality Index (PSQI): A new instrument for psychiatric research and practice. Psychiatry Res. 1989; May; 28(2):193–213. doi: 10.1016/0165-1781(89)90047-4. PMID: 2748771.
Yost KJ, Eton DT. Combining distribution- and anchor-based approaches to determine minimally important differences: the FACIT experience. Eval Health Prof. 2005; Jun;28(2):172 – 91. doi: 10.1177/0163278705275340. PMID: 15851772.
Pearman T, Yanez B, Peipert J, et al. Ambulatory cancer and US general population reference values and cutoff scores for the functional assessment of cancer therapy. Cancer. 2014; Sep 15;120(18):2902–9. doi: 10.1002/cncr.28758. Epub 2014 May 22. PMID: 24853866.
Westin SN, Sun CC, Tung CS, Lacour RA, Meyer LA, Urbauer DL, Frumovitz MM, Lu KH, Bodurka DC. Survivors of gynecologic malignancies: impact of treatment on health and well-being. J Cancer Surviv. 2016; Apr;10(2):261–70. doi: 10.1007/s11764-015-0472-9. Epub 2015 Aug 6. PMID: 26245979; PMCID: PMC4744585.
Savard J, Davidson JR, Ivers H, Quesnel C, Rioux D, Dupéré V, Lasnier M, Simard S, Morin CM. The association between nocturnal hot flashes and sleep in breast cancer survivors. J Pain Symptom Manage. 2004; Jun;27(6):513 – 22. doi: 10.1016/j.jpainsymman.2003.10.013. PMID: 15165649.
Glaus A, Boehme Ch, Thürlimann B, Ruhstaller T, Hsu Schmitz SF, Morant R, Senn HJ, von Moos R. Fatigue and menopausal symptoms in women with breast cancer undergoing hormonal cancer treatment. Ann Oncol. 2006; May;17(5):801–6. doi: 10.1093/annonc/mdl030. Epub 2006 Feb 28. PMID: 16507565.
Matthews KA, Hall MH, Lee L, et al. Racial/ethnic disparities in women's sleep duration, continuity, and quality, and their statistical mediators: Study of Women's Health Across the Nation. Sleep. 2019; May 1;42(5). doi: 10.1093/sleep/zsz042. PMID: 30778560; PMCID: PMC6519910.
Wong E, Rowbottom L, Tsao M, et al. Prognostic value of pre- and post-treatment health-related quality of life in predicting survival of patients with brain metastases. CNS Oncol. 2017; Apr;6(2):119–129. doi: 10.2217/cns-2016-0020.
Karvonen-Gutierrez CA, Ronis DL, Fowler KE, et al. Quality of life scores predict survival among patients with head and neck cancer. J Clin Oncol. 2008; Jun 1;26(16):2754-60. doi: 10.1200/JCO.2007.12.9510. PMID: 18509185.
Epplein M, Zheng Y, Zheng W, et al. Quality of life after breast cancer diagnosis and survival. J Clin Oncol. 2011; Feb 1;29(4):406 – 12. doi: 10.1200/JCO.2010.30.6951.

No competing interests reported.

ECantilloChemoandSleepSupplementary.docx

Download PDF

Editorial decision: Revision requested
24 May, 2024
Reviews received at journal
24 May, 2024
Reviewers agreed at journal
22 Apr, 2024
Reviewers invited by journal
19 Mar, 2024
Editor assigned by journal
19 Mar, 2024
Submission checks completed at journal
20 Feb, 2024
First submitted to journal
04 Feb, 2024

You are reading this latest preprint version

A Prospective Study of Sleep Quality in Women Undergoing Chemotherapy for Breast, Ovarian, and Endometrial Cancer

Status:

Version 1

Abstract

Figures

Introduction

Methods

Measures

Statistical Analysis

Results

Participation and Protocol Adherence

Demographics and Clinical Characteristics

Sleep

Quality of Life

Associations between Sleep and QOL

Discussion

Declarations

Conflicts of Interest:

Funding:

Author Contribution

References

Additional Declarations

Supplementary Files

Status:

Version 1