Do cancer survivors develop healthier lifestyle behaviors than the cancer-free population in the PLCO study?

Physical Activity Among Utah Cancer Survivors: Analysis From a Population-Based Statewide Survey

BACKGROUND

Regular physical activity improves cancer survivors' health-related quality of life and physical function. We estimated the proportion of Utah cancer survivors meeting U.S. Department of Health and Human Services guidelines for weekly physical activity (aerobic plus strength exercise) and identify sociodemographic, cancer, and health-related factors associated with meeting guidelines.

METHODS

Survivors randomly sampled from Utah Cancer Registry records were surveyed from 2018 to 2022 to ascertain physical activity. We calculated the percent of survivors meeting guidelines and conducted logistic regression to assess predictors of meeting guidelines. Analyses were weighted to account for complex survey sample design and nonresponse and age adjusted.

RESULTS

Among Utah cancer survivors, 20.7% (95% CI, 18.5%-23.2%) met guidelines for both aerobic activity and strength exercise. 22.4% reported no aerobic exercise in a typical week, and 59.4% reported no strength exercise. Survivors 75 or older were less likely to meet physical activity guidelines than those under 55 (adjusted odds ratio: 0.40; 95% CI, 0.25-0.65). Survivors with a bachelor's degree or higher were more likely to meet physical activity guidelines than those without a college degree. Individuals with poorer overall health were less likely to report sufficient physical activity. Individuals treated with both chemotherapy and radiation had decreased odds of meeting guidelines compared to no treatment (adjusted odds ratio: 0.54; 95% CI, 0.29-0.99).

CONCLUSIONS

Most Utah cancer survivors, and particularly those who received multiple modes of adjuvant treatment, are not participating in sufficient physical activity to improve longevity and quality of life after cancer.

Preventive behaviors and behavioral risk factors among gynecologic cancer survivors: Results from the 2020 Behavioral Risk Factor Surveillance System Survey

BACKGROUND

Maintaining a healthy lifestyle is an important factor in promoting positive outcomes for gynecologic cancer survivors.

METHODS

We examined preventive behaviors among gynecologic cancer survivors (n = 1824) and persons without a history of cancer in a cross-sectional analysis, using data from the 2020 Behavioral Risk Factor Surveillance System survey (BRFSS). BRFSS is a cross-sectional telephone-based survey of U.S. residents 18 years of age and older, which collects information about health-related factors and use of preventive services.

RESULTS

The prevalence rates of colorectal cancer screening were respectively 7.9 (95% CI: 4.0-11.9) and 15.0 (95% CI: 4.0-11.9) %-points higher among gynecologic and other cancer survivors compared to that of 65.2% among those without any history of cancer. However, no differences were observed in breast cancer screening between gynecologic cancer survivors (78.5%) and respondents without any history of cancer (78.7%). Coverage of influenza vaccination among gynecologic cancer survivors were 4.0 (95% CI: 0.3-7.6) %-points higher than that of the no cancer group, but 11.6 (95% CI: 7.6-15.6) %-points lower than that of the other cancer group. Pneumonia vaccination rate among gynecologic cancer survivors, however, was not statistically different than that of other cancer survivors and respondents with no history of cancer. When examining modifiable risk behaviors, the prevalence of smoking among gynecologic cancer survivors was 12.8 (95% CI: 9.5-16.0) and 14.2 (95% CI: 10.8-17.7) %-points higher than smoking prevalence among other cancer survivors and respondents without any history of cancer. The rate differentials were even higher in rural areas, 17.4 (95% CI: 7.2-27.6) and 18.4 (95% CI: 7.4-29.4) %-points respectively. There were no differences in the prevalence of heavy drinking across the groups. Lastly, gynecologic and other cancer survivors were less likely to be physically active (Δ = -12.3, 95% CI: -15.8 to -8.8 and Δ = -6.9, 95% CI: -8.5 to -5.3, respectively) than those without any history of cancer.

CONCLUSION

Smoking prevalence among gynecologic cancer survivors is alarmingly high. Intervention studies are needed to identify effective ways to assist gynecologic cancer survivors to quit smoking and refrain from hazardous alcohol consumption. In addition, women with gynecologic malignancies should made aware of the importance of physical activity.

Higher Incidence of Diabetes in Cancer Patients Compared to Cancer-Free Population Controls: A Systematic Review and Meta-Analysis

Background: Diabetes increases the risk of certain types of cancer. However, the literature regarding the incidence of diabetes after cancer diagnosis is inconsistent. We aimed to assess whether there was a higher incidence of diabetes among cancer patients by performing a systematic review and meta-analysis of results from cohort studies. Methods: A systematic electronic literature search was carried out from cohort studies regarding the incidence of diabetes in cancer patients, using the databases PubMed (MEDLINE), Embase, Web of Science, and the Cochrane Library. Random-effects meta-analyses were conducted to pool the estimates. Results: A total of 34 articles involving 360,971 cancer patients and 1,819,451 cancer-free controls were included in the meta-analysis. An increased pooled relative risk (RR) of 1.42 (95% confidence interval (CI): 1.30−1.54, I2 = 95, τ2 = 0.0551, p < 0.01) for diabetes in cancer patients was found compared with the cancer-free population. The highest relative risk was observed in the first year after cancer diagnosis (RR = 2.06; 95% CI 1.63−2.60). Conclusions: New-onset diabetes is positively associated with cancer, but this association varies according to cancer type. More prospective studies with large sample sizes and longer follow-up times are advocated to further examine the association and the underlying mechanisms.

Colorectal Cancer Survivors' Receptivity toward Genomic Testing and Targeted Use of Non-Steroidal Anti-Inflammatory Drugs to Prevent Cancer Recurrence

Genomic testing and targeted use of non-steroidal anti-inflammatory drugs (NSAIDs) may mitigate cancer recurrence risks. This study examines colorectal cancer (CRC) survivors' interest and receptivity to these strategies. Patients diagnosed with stage I-III CRC in 2004-2012 were recruited through the New Mexico Cancer Registry to complete a cancer survivorship experiences survey. We assessed interest in genomic testing, daily aspirin (ASA) and NSAID use, and receptivity to future daily ASA/NSAIDs. Descriptive statistics and multivariable logistic regression models estimated factors associated with genomic testing interest. Receptivity to future ASA/NSAIDs use was estimated for non-users of ASA/NSAIDs. Among CRC survivors (n = 273), 83% endorsed interest in genomic testing, 25% were ASA users and 47% ASA/NSAIDs users. In our final model, genomic testing interest was associated with being uncoupled [OR = 4.11; 95% CI = 1.49-11.35], low income [OR = 0.35, 95% CI: 0.14-0.88], smoking history [OR = 0.35, 95% CI: 0.14-0.90], low [OR: 0.33, 95% CI: 0.07-1.43] and moderate [OR: 0.26, 95% CI: 0.11-0.61] health literacy, and personal CRC risk worry [OR: 2.86, 95% CI: 1.63-5.02, p = 0.0002]. In our final model, ASA use was associated with age [OR: 1.05, 95% CI: 1.01-1.10] and cardiovascular disease history [OR: 2.42, 95% CI: 1.23-4.73, p = 0.010]. Among non-users ASA/NSAIDs, 83% reported receptivity to ASA/NSAIDs to reduce cancer risks, and no significant correlates were identified. The majority of survivors' expressed genomic testing interest and endorsed receptivity toward ASA/NSAIDs use for cancer risk management. Further research to optimize ASA/NSAIDs use guided by genomic testing is warranted.

E-cigarette and cigarette use among cancer survivors versus general population: a case-control study in Korea

PURPOSE

Although successful smoking cessation after cancer diagnosis is important, research on e-cigarette use and smoking behavior among cancer survivors (CS) is limited. This study compared cigarette and e-cigarette use among CS and non-cancer populations in Korea.

METHODS

This study analyzed the 2013-2018 National Health and Nutrition Survey data to investigate e-cigarette use and smoking behavior among Korean CS. The data were categorized into 1260 CS and 5040 non-cancer populations using the propensity score matching method. A multiple logistic regression was conducted among CS who previously used cigarettes or e-cigarettes to evaluate factors influencing successful cessation.

RESULTS

Regarding conventional smoking, the proportion of ex-smokers was higher (25.2% versus 19.9%) than current smokers (6.7% versus 10.6%) in the CS group than in the propensity matched non-cancer population (PMNCP) (p < 0.001). However, ever use of e-cigarettes did not differ between them (2.4% versus 2.7%, p = 0.529). Successful cessation, defined as not using either cigarettes or e-cigarettes, correlated with problem drinking (OR 0.442, 95% CI 0.207-0.940), depression (OR 0.276, 95% CI 0.087-0.872), and cancer sites. CS of stomach, liver, colorectal, and lung cancer maintained higher successful smoking cessation rates than PMNCP.

CONCLUSIONS

Korean CS had a higher cessation rate than PMNCP regarding conventional smoking; however, there was no difference in e-cigarette use.

IMPLICATIONS FOR CANCER SURVIVORS

In Korea, some CS continue to use e-cigarettes, and physicians should focus on helping them quit. Individualized and timely interventions should be provided for both cigarette and e-cigarette users, considering factors influencing successful cessation.

A Classification Approach for Cancer Survivors from Those Cancer-Free, Based on Health Behaviors: Analysis of the Lifelines Cohort

Simple Summary

Health behaviors affect health status in cancer survivors. We aimed to identify such key health behaviors using nonlinear algorithms and compare their classification performance with logistic regression, for distinguishing cancer survivors from those cancer-free in a population-based cohort. We used health behaviors and socioeconomic factors for analysis. Participants from the Lifelines population-based cohort were binary classified as cancer survivors or cancer-free using nonlinear algorithms or logistic regression. Data were collected for 107,624 cancer-free participants and 2760 cancer survivors. Using all variables, algorithms obtained an area under the receiver operator curve (AUC) of 0.75 ± 0.01. Using only health behaviors, the algorithms differentiated cancer survivors from cancer-free participants with AUCs of 0.62 ± 0.01 and 0.60 ± 0.01, respectively. In the case–control analyses, both algorithms produced AUCs of 0.52 ± 0.01. The main distinctive classifier was age. No key health behaviors were identified by linear and nonlinear algorithms to differentiate cancer survivors from cancer-free participants.

Abstract

Health behaviors affect health status in cancer survivors. We hypothesized that nonlinear algorithms would identify distinct key health behaviors compared to a linear algorithm and better classify cancer survivors. We aimed to use three nonlinear algorithms to identify such key health behaviors and compare their performances with that of a logistic regression for distinguishing cancer survivors from those without cancer in a population-based cohort study. We used six health behaviors and three socioeconomic factors for analysis. Participants from the Lifelines population-based cohort were binary classified into a cancer-survivors group and a cancer-free group using either nonlinear algorithms or logistic regression, and their performances were compared by the area under the curve (AUC). In addition, we performed case–control analyses (matched by age, sex, and education level) to evaluate classification performance only by health behaviors. Data were collected for 107,624 cancer free participants and 2760 cancer survivors. Using all variables resulted an AUC of 0.75 ± 0.01, using only six health behaviors, the logistic regression and nonlinear algorithms differentiated cancer survivors from cancer-free participants with AUCs of 0.62 ± 0.01 and 0.60 ± 0.01, respectively. The main distinctive classifier was age. Though not relevant to classification, the main distinctive health behaviors were body mass index and alcohol consumption. In the case–control analyses, algorithms produced AUCs of 0.52 ± 0.01. No key health behaviors were identified by linear and nonlinear algorithms to differentiate cancer survivors from cancer-free participants in this population-based cohort.

An Association Rule Mining Analysis of Lifestyle Behavioral Risk Factors in Cancer Survivors with High Cardiovascular Disease Risk

We aimed to assess which lifestyle risk behaviors have the greatest influence on the risk of cardiovascular disease in cancer survivors and which of these behaviors are most prominently clustered in cancer survivors, using logistic regression and association rule mining (ARM). We analyzed a consecutive series of 897 cancer survivors from the Korean National Health and Nutritional Exam Survey (2012-2016). Cardiovascular disease risks were assessed using the atherosclerotic cardiovascular disease score (ASCVDs). We classified participants as being in a low-risk group if their calculated ASCVDs was less than 10% and as being in a high-risk group if their score was 10% or higher. We used association rule mining to analyze patterns of lifestyle risk behaviors by ASCVDs risk group, based upon public health recommendations described in the Alameda 7 health behaviors (current smoking, heavy drinking, physical inactivity, obesity, breakfast skipping, frequent snacking, and suboptimal sleep duration). Forty-two percent of cancer survivors had a high ASCVD. Current smoking (common odds ratio, 11.19; 95% confidence interval, 3.66-34.20, p < 0.001) and obesity (common odds ratio, 2.67; 95% confidence interval, 1.40-5.08, p < 0.001) were significant predictors of high ASCVD in cancer survivors within a multivariate model. In ARM analysis, current smoking and obesity were identified as important lifestyle risk behaviors in cancer survivors. In addition, various lifestyle risk behaviors co-occurred with smoking in male cancer survivors.

Healthy Behaviors: Prevalence of Uptake Among Cancer Survivors

BACKGROUND

Although most cancer survivors adhere to recommendations to refrain from tobacco and minimize alcohol use, survivors of certain cancers are not meeting these recommendations. In addition, most cancer survivors do not achieve optimal recommendations for diet and physical activity, further decreasing survivor health and quality of life. Sun protective and sleep behaviors also tend to be suboptimal among survivors. Uptake of age-appropriate vaccinations is variable among survivors.

OBJECTIVES

The purpose of this article is to review the prevalence of healthy behavior uptake among cancer survivors and provide nurses with an overview of effective interventions, strategies, and resources to help patients improve these behaviors.

METHODS

An expert panel was convened to conduct an integrative review and synthesis on the state of the science of healthy behavior uptake among cancer survivors.

FINDINGS

Not meeting recommendations for healthy lifestyle behaviors increases the risk of second cancers and mortality and decreases overall health and quality of life. Healthy lifestyle behaviors can contribute to improved function, quality of life, and overall survival for cancer survivors. Nurses can help survivors to understand and improve their behaviors.

Diet and nutrition information and support needs in pelvic radiotherapy: A systematic, mixed-methods review

INTRODUCTION

This study aimed to review diet and nutrition information and support needs of cancer patients who receive pelvic radiotherapy to inform the development of interventions to improve this area of care.

METHODS

The systematic review followed the PRISMA guidelines. Six electronic databases were searched for peer-reviewed studies of any design that assessed diet and nutrition needs after a pelvic cancer diagnosis. Narrative synthesis was used to integrate findings.

RESULTS

Thirty studies (12 quantitative, 15 qualitative, 3 mixed-methods) were included. Four themes, "content of dietary information"; "sources of information"; "sustaining dietary change"; and "views on the role of diet post-treatment," summarised evidence about provision of nutritional guidance following diagnosis, but also contrasting views about the role of diet post-diagnosis. Qualitative studies contributed considerably more to the synthesis, compared to quantitative studies. Included studies were of moderate to good quality; selection bias in quantitative studies and poor evidence of credibility and dependability in qualitative studies were highlighted.

CONCLUSION

There is some evidence of lack of nutrition support in pelvic cancer survivors, but methodological limitations of included studies may have had an impact on the findings. Future, prospective studies that focus on diet and nutrition needs post-diagnosis are warranted to improve care.

What happens to cancer survivors attending a structured cancer survivorship clinic? Symptoms, quality of life and lifestyle changes over the first year at the Sydney Cancer Survivorship Centre clinic

BACKGROUND

Sydney Cancer Survivorship Centre (SCSC) clinic provides multidisciplinary care after primary adjuvant treatment, with ~ 40% of attendees continuing follow-up with SCSC.

METHODS

SCSC survivors completed measures of symptoms, quality-of-life and lifestyle factors at initial visit (T1), first follow-up (T2) and 1 year (T3). Analyses used mixed effect models, adjusted for age, sex and tumour type.

RESULTS

Data from 206 survivors (2013-2019) were included: 51% male; median age 63 years; tumour types colorectal 68%, breast 12%, upper gastrointestinal 12%, other 8%. Mean time from: T1 to T2, 3.6 months; T1 to T3, 11.8 months. Mean weight remained stable, but 45% (35/77) of overweight/obese survivors lost weight from T1 to T3. Moderately-intense aerobic exercise increased by 63 mins/week at T2, and 68 mins/week T3. Proportion meeting aerobic exercise guidelines increased from 20 to 41%. Resistance exercise increased by 26 mins/week at T2. Global quality-of-life was unchanged from T1 to T2, improving slightly by T3 (3.7-point increase), mainly in males. Mean distress scores were stable, but at T3 the proportion scoring 4+/10 had declined from 41 to 33%. At T3, improvements were seen in pain, fatigue and energy, but > 20% reported moderate-severe fatigue, pain or sleep disturbance. Proportion reporting 5+ moderate-severe symptoms declined from 35% at T1 to 26% at T3, remaining higher in women.

CONCLUSIONS

Survivors attending SCSC increased exercise by 3 months, and sustained it at 1 year. Most overweight/obese survivors avoided further weight gain. Survivors had relatively good quality-of-life, with improvement in many symptoms and lifestyle factors at 1 year.

Multiple health behaviors before and after a cancer diagnosis among women: A repeated cross-sectional analysis over 15 years

Background

Cancer diagnosis may be a cue for health behavior change. Previous research that assessed the impact of a cancer diagnosis on multiple health behavior (MHB) change is limited by small sample size, cross‐sectional study design, and a focus on individual rather than multiple behaviors. This study investigated the impact of a cancer diagnosis on compliance with MHB recommendations.

Methods

Data from Australian Longitudinal Study on Women's Health (ALSWH) were utilized. Compliance with MHB was assessed by cancer survivorship period; 0‐3 years pre‐diagnosis, 0‐3 years postdiagnosis, 4‐12 years postdiagnosis, and compared to controls. A MHB score based on the WCRF/AICR guidelines was calculated for six behaviors (physical activity, smoking, alcohol, BMI, fruit, and vegetable intake); scores ranged from 0 to 6, with a higher score indicating higher compliance. Generalized estimating equation (GEE) was used for statistical analysis.

Results

Participants comprised 7585 women from the 2001 ALSWH survey, of whom 2285 developed cancer during 15 years of follow‐up. Compared to controls, the mean MHB score was slightly lower (Mean Difference (MD) = −0.015, P > .05) in survivors pre‐diagnosis, after adjusting for confounders; however, the compliance score increased during postdiagnosis, with the mean difference score being significantly higher in recent survivors (0‐3 years post diagnosis; MD = 0.055, P < .01). Likewise, within cancer survivors, the mean compliance score significantly increased 0‐3 years postdiagnosis (MD = 0.07, P < .05) compared to pre‐diagnosis, but this significant improvement was not maintained over the longer term (MD = 0.037, P > .05).

Conclusion

In this sample, survivors had higher MHB score than controls. A cancer diagnosis may provide a teachable moment for health behavior change in the period immediately following diagnosis, but this effect was not sustained during longer‐term survivorship.

Endocrine and Metabolic Diseases Among Colorectal Cancer Survivors in a Population-Based Cohort

BACKGROUND

There are an estimated 1.4 million colorectal cancer (CRC) survivors in the United States. Research on endocrine and metabolic diseases over the long term in CRC survivors is limited. Obesity is a risk factor for CRC; thus it is of interest to investigate diseases that may share this risk factor, such as diabetes, for long-term health outcomes among CRC survivors.

METHODS

A total of 7114 CRC patients were identified from the Utah Population Database and matched to a general population cohort of 25 979 individuals on birth year, sex, and birth state. Disease diagnoses (assessed over three time periods of 1-5 years, 5-10 years, and >10 years) were identified using electronic medical records and statewide ambulatory and inpatient discharge data. Cox proportional hazard models were used to estimate the risk of endocrine and metabolic disease.

RESULTS

Across all three time periods, risks for endocrine and metabolic diseases were statistically significantly greater for CRC survivors compared with the general population cohort. At 1-5 years postdiagnosis, CRC survivors' risk for diabetes mellitus with complications was statistically significantly elevated (hazard ratio [HR] = 1.36, 99% confidence interval [CI] = 1.09 to 1.70). CRC survivors also experienced a 40% increased risk of obesity at 1-5 years postcancer diagnosis (HR= 1.40, 99% CI= 1.66 to 2.18) and a 50% increased risk at 5-10 years postdiagnosis (HR = 1.50, 99% CI= 1.16 to 1.95).

CONCLUSIONS

Endocrine and metabolic diseases were statistically significantly higher in CRC survivors throughout the follow-up periods of 1-5 years, 5-10 years, and more than 10 years postdiagnosis. As the number of CRC survivors increases, understanding the long-term trajectory is critical for improved survivorship care.

Continued smoking after a cancer diagnosis: a longitudinal study of intentions and attempts to quit

PURPOSE

Continued smoking after a cancer diagnosis is associated with poor treatment outcomes and reduced life expectancy. We aimed to identify the stability of smoking status after diagnosis including quit attempts and quit intentions.

METHODS

Participants with a first primary cancer diagnosis were recruited via two state-based registries in Australia. Questionnaires were mailed at approximately 6 months (T1), 1 year (T2), 2 years (T3), and 3.5 years (T4) post-diagnosis. Smoking status and quitting intentions were assessed at each time point.

RESULTS

A cohort of 1444 people was recruited. People who indicated that they were more than 9 months post-diagnosis are excluded from analysis, leaving 1407 eligible study participants. Sixty-six (37%) of the 178 self-reported smokers at diagnosis had quit in the 6-month post-diagnosis (T1), the remaining 112 (63%) reported being a current smoker. Of the smokers at T1, 40% intended to quit: with 8% having quit smoking by T2; 11% quit by T3; 12% quit by T4. Of those who reported at T1 that they intended to quit in the next 6 months, 10% or fewer reported having quit at any subsequent time point. Quitting attempts decreased in frequency over time post-diagnosis. Less than 15% of respondents who had quit at or shortly before diagnosis reported relapse to smoking at each time point.

CONCLUSIONS

The majority of smokers diagnosed with cancer continue to smoke beyond diagnosis, even in the context of an intention to quit and attempts to do so. Cancer survivors who smoke remain motivated to quit well beyond the initial diagnosis.

IMPLICATIONS FOR CANCER SURVIVORS

There are clear positive clinical effects of smoking cessation for those who have undergone treatment for cancer, both for short-term treatment outcomes, and for long-term survivorship. Given the substantial rates of continued smoking among those who report smoking at diagnosis and their continued attempts to quit during survivorship, there is a need for improved cessation support initiatives for people diagnosed with cancer. These initiatives need to continue to be offered to smokers long after the initial diagnosis and treatment.

Compliance with Multiple Health Behaviour Recommendations: A Cross-Sectional Comparison between Female Cancer Survivors and Those with no Cancer History

Lifestyle behaviours have an important role in preventing cancer, reducing treatment side effects, and improving survival and quality of life for cancer survivors. This study investigated adherence to multiple lifestyle behaviours among women with and without a cancer history. From the Australian Longitudinal Study on Women’s Health (ALSWH) surveys, 2407 cancer survivors and 3896 controls (cancer free population) were identified. Based on the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) recommendations, adherence to six health behaviours (smoking, physical activity, fruit and vegetable intake, alcohol consumption, sugary drink intake, and Body Mass Index [BMI]) were assessed. Overall adherence was low, and there were no differences between survivors and controls on adherence to any of the six individual health behaviours. However, both recent and long-term cancer survivors were more likely than controls to adhere to multiple health behaviours (p < 0.05). When participants with melanoma or non-melanoma skin cancer were excluded, adherence was less likely (but not significant) in the cancer group than controls. Higher education (p < 0.01), being married (p < 0.01), and lower comorbidity of chronic illnesses (p < 0.01) were significantly associated with adherence to multiple lifestyle behaviours. Overall, the findings suggest that a cancer diagnosis may result in increased compliance with multiple health behaviour guidelines.