Prevalence of multimorbidity in adults with cancer, and associated health service utilization in Ontario, Canada: a population-based retrospective cohort study

Indirect effects of health-related quality of life on suicidal ideation through psychological distress among cancer patients

The interrelationships of suicidal ideation, psychological distress, and impaired health-related quality of life (HRQoL) in cancer patients are complex and multifaceted. Limited empirical evidence exists on the indirect effects of impaired HRQoL on suicidal ideation through psychological distress among cancer patients. To fill this research gap, 250 cancer patients were recruited through a cross-sectional hospital-based research design. Structural equation model (SEM) results indicated that impaired HRQoL is a predictor of psychological distress (β = 0.153; p < 0.05), and psychological distress positively predicts suicidal ideation (β = 0.647; p < 0.000). The study found no direct effects of impaired HRQoL on suicidal ideation (β = -0.05; p = 0.223). Indirect effects of HRQoL on suicidal ideation was confirmed, showing a full-mediation effect β = 0.099 (SE = 0.048, CI = [0.030, 0.189], p < 0.05) (i.e. the pathway impaired HRQoL predict suicidal ideation is through psychological distress). Cognitive-behavioral therapy and other emotional support programs should be considered for cancer patients to mitigate psychological vulnerabilities linking impaired HRQoL to suicidal ideation.

Interaction between depressive symptoms and obesity-related anthropometric measures on multimorbidity among community-dwelling older adults: evidence from India

BACKGROUND

This study aimed to examine the associations between depressive symptoms, body mass index (BMI), waist circumference, waist-hip ratio and multimorbidity among community-dwelling older adults. We also examine the interaction effects between depressive symptoms, BMI, waist circumference and waist-hip ratio on multimorbidity among older adults in India.

METHODS

A cross-sectional study was conducted, and the data were obtained from the Longitudinal Ageing Study in India (LASI) wave-1, with a sample of 31,464 older adults aged 60 years and above (men-15,098 and women-16,366). We used multinomial logistic regression to explore the independent associations between depressive symptoms, obesity-measures, and single and multimorbidity. We also estimated the interaction effects of depressive symptoms and obesity-measures on multimorbidity.

RESULTS

The prevalence of multimorbidity was higher among individuals with depressive symptoms (39.22%) than individuals with no depressive symptoms (29.94%). Adjusted models indicated that older adults with depressive symptoms had higher odds of single and multimorbidity [(AOR = 1.40, 95% CI: 1.17-1.68) and (AOR = 1.85, 95% CI: 1.58-2.16), respectively]. Similarly, in comparison to the normal BMI category, overweight and obese older adults were more likely to report single morbidity [(AOR = 1.62, 95% CI: 1.37-1.92 and (AOR = 2.14, 95% CI: 1.67-2.75), respectively] and multimorbidity [(AOR = 2.00, 95% CI: 1.72-2.33) and (AOR = 3.77, 95% CI: 2.94-4.82), respectively].

CONCLUSION

The findings revealed that the presence of depressive symptoms, overweight or obesity, and high-risk anthropometric measures such as high-risk waist circumference and high-risk waist to hip ratio significantly increased the risk of morbidity among older adults in India. Thus, it is suggested to adopt an integrated public health policy approach to control depressive symptoms and high-risk body composition to strategically prepare against the elevated risk of multimorbidity among ageing populations.

Understanding the Extent of Polypharmacy and its Association With Health Service Utilization Among Persons With Cancer and Multimorbidity: A Population-Based Retrospective Cohort Study in Ontario, Canada

Background: Cancer often co-occurs with other chronic conditions, which may result in polypharmacy. Polypharmacy is associated with adverse outcomes, including increased health service utilization. Objectives: This study examines the overall prevalence of polypharmacy (5 or more medications) among adults with cancer and multimorbidity, as well as the association of both minor polypharmacy (5-9 medications) and hyper-polypharmacy (10 or more medications) on high use of emergency room visits and hospitalizations, while controlling for age, sex, and type and stage of cancer. Methods: This retrospective longitudinal study used linked health administrative databases and included persons 18 years and older diagnosed with cancer between April 2010 and March 2013 in Ontario, Canada. Data on the number of health service utilizations at or above the 90th percentile (high users), was collected up to March 2014 and multivariate logistic regression was used to determine the impact of polypharmacy. Results: The prevalence of polypharmacy was 46% prior to cancer diagnosis, and 57% one year after diagnosis. Polypharmacy prior to and after cancer diagnosis increased with the level of multimorbidity, increasing age, but did not differ by sex. It was also highest in persons with lung cancer (52.4%) and those diagnosed with stage 4 cancer (51.3%). Minor polypharmacy increased the odds of being a high user of emergency rooms (1.16; 99% CI: 1.09-1.24) and hospitalizations (1.03; 0.98-1.09) and the odds of high use was greater with hyper-polypharmacy (1.41; 1.33-1.51) and (1.23; 1.17-1.29) respectively. Conclusion: Polypharmacy is highly prevalent and is associated with high health service utilization among adults with cancer and multimorbidity.

Rationalizing prescription via deprescribing in oncology practice

OBJECTIVE

To provide an integrated approach for deprescribing practice in oncology setting.

DATA SOURCES

The data on deprescribing in oncology settings has been retrieved from the PubMed, Scopus and Google Scholar. We used "deprescribing," "potentially inappropriate medication" and "cancer" as a keyword for the conducting general search. The articles relevant to guidelines or tools used to deprescribe in cancer care were included.

DATA SUMMARY

The nature of cancer, its treatment strategies, adverse effects of therapy and multimorbidity impact negatively on quality of life (QoL). Further, they invite polypharmacy which puts the patient at higher risk of drug-related problems like drug interactions, adverse drug reactions and addition of potentially improper medications, etc. In older adults with cancer, the incidence of potentially inappropriate medications (PIMs) was between 41% and 52%. Over the decades, multiple strategies have been developed to assess the appropriateness of therapy. One such approach is deprescribing. OncPal and oncoSTRIP (Systematic Tool to Reduce Inappropriate Prescribing) are the cancer specific guidelines whereas BEERs criteria, Screening Tool to Alert to Right Treatment/Screening Tool of Older Person's Prescriptions criteria (START/STOPP criteria), medication appropriateness index (MAI) are the cancer nonspecific tools to identify PIM among cancer patients. Here, we provided an integrative approach and algorithm for deprescribing in oncology setting which includes patient and caregiver goals, life expectancy (LE), review of medications, determining medication appropriateness, assessment of time to benefit (TTB), symptomatic and asymptomatic care, identifying medications to cease, implementation of the plan, monitoring and reviewing.

CONCLUSION

Deprescribing in oncology setting is a novel and effective patient-centric approach to counteract the use of PIM, which helps to mitigate polypharmacy, drug-drug interactions, and adverse effects.

Are breast cancer patients with suboptimal adherence to cardiovascular treatment more likely to discontinue adjuvant endocrine therapy? Competing risk survival analysis in a nationwide cohort of postmenopausal women

BACKGROUND

High rates of discontinuation undermine the effectiveness of adjuvant endocrine therapy (AET) among hormone-receptive breast cancer patients. Patient prognosis also relies on the successful management of cardiovascular risk, which affects a high proportion of postmenopausal women. As with AET, adherence with cardiovascular drugs is suboptimal. We examined whether patient adherence with cardiovascular drugs was associated with the rate of AET discontinuation in a French nationwide claims database linked with hospitalisation data.

METHODS

We identified postmenopausal women starting AET between 01/01/2016 and 31/12/2020 and taking at least two drugs for the primary prevention of cardiovascular disease (antihypertensive drugs, lipid-lowering drugs and platelet aggregation inhibitors) before AET initiation. Adherence was assessed for each drug class by computing the proportion of days covered. Women were categorised as fully adherent, partially adherent or fully non-adherent with their cardiovascular drug regimen based on whether they adhered with all, part or none of their drugs. AET discontinuation was defined as a 90-day gap in AET availability. Time to AET discontinuation according to levels of cardiovascular drug adherence was estimated using cumulative incidence curves, accounting for the competing risks of death and cancer recurrence. Multivariate cause-specific Cox regressions and Fine-and-Gray regressions were used to assess the relative hazards of AET discontinuation.

RESULTS

In total, 32,075 women fit the inclusion criteria. Women who were fully adherent with their cardiovascular drugs had the lowest cumulative incidence of AET discontinuation at any point over the 5-year follow-up period. At 5 years, 40.2% of fully non-adherent women had discontinued AET compared with 33.5% of partially adherent women and 28.8% of fully adherent women. Both partial adherence and full non-adherence with cardiovascular drugs were predictors of AET discontinuation in the two models (cause-specific hazard ratios 1.16 [95% CI 1.10-1.22] and 1.49 [95% CI 1.39-1.58]; subdistribution hazard ratios 1.15 [95% CI 1.10-1.21] and 1.47 [95% CI 1.38-1.57]).

CONCLUSION

Clinicians should be aware that patients who do not adhere with their entire cardiovascular drug regimen are also more likely to discontinue AET. This stresses the importance of integrated care, as suboptimal adherence with both treatment components poses a threat to achieving ideal patient outcomes.

Multi-morbidity and its association with common cancer diagnoses: a UK Biobank prospective study

BACKGROUND

Whilst multi-morbidity is known to be a concern in people with cancer, very little is known about the risk of cancer in multi-morbid patients. This study aims to investigate the risk of being diagnosed with lung, colorectal, breast and prostate cancer associated with multi-morbidity.

METHODS

We investigated the association between multi-morbidity and subsequent risk of cancer diagnosis in UK Biobank. Cox models were used to estimate the relative risks of each cancer of interest in multi-morbid participants, using the Cambridge Multimorbidity Score. The extent to which reverse causation, residual confounding and ascertainment bias may have impacted on the findings was robustly investigated.

RESULTS

Of the 436,990 participants included in the study who were cancer-free at baseline, 21.6% (99,965) were multi-morbid (≥ 2 diseases). Over a median follow-up time of 10.9 [IQR 10.0-11.7] years, 9,019 prostate, 7,994 breast, 5,241 colorectal, and 3,591 lung cancers were diagnosed. After exclusion of the first year of follow-up, there was no clear association between multi-morbidity and risk of colorectal, prostate or breast cancer diagnosis. Those with ≥ 4 diseases at recruitment had double the risk of a subsequent lung cancer diagnosis compared to those with no diseases (HR 2.00 [95% CI 1.70-2.35] p for trend < 0.001). These findings were robust to sensitivity analyses aimed at reducing the impact of reverse causation, residual confounding from known cancer risk factors and ascertainment bias.

CONCLUSIONS

Individuals with multi-morbidity are at an increased risk of lung cancer diagnosis. While this association did not appear to be due to common sources of bias in observational studies, further research is needed to understand what underlies this association.

Financial well-being as a mediator of the relationship between multimorbidity and health-related quality of life in people with cancer

BACKGROUND

It is unknown whether financial well-being mediates the impact of multimorbidity on the health-related quality of life (HRQoL) of cancer patients.

METHODS

Participants were recruited from three outpatient oncology clinics of Hong Kong public hospitals. Multimorbidity was assessed using the Charlson Comorbidity Index. Financial well-being, the mediator of the association between multimorbidity and HRQoL outcomes, was assessed using the Comprehensive Score for Financial Toxicity Functional Assessment of Chronic Illness Therapy. The HRQoL outcomes were assessed using the Functional Assessment of Cancer Therapy - General (FACT-G) and its four sub-dimensions. Mediation analyses were conducted using SPSS PROCESS v4.1.

RESULTS

Six-hundred and forty cancer patients participated in the study. Multimorbidity had a direct effect on FACT-G scores independent of financial well-being (β for path c' = -0.752, p < 0.001). In addition, multimorbidity had an indirect effect on FACT-G scores through its effect on financial well-being (β for path a = -0.517, p < 0.05; β for path b = 0.785, p < 0.001). Even after adjustments were made for the covariates, the indirect effect of multimorbidity on FACT-G via financial well-being remained significant, accounting for 38.0% of the overall effect, indicating partial mediation. Although there were no statistically significant associations between multimorbidity, social well-being, and emotional well-being, the indirect effects of multimorbidity on physical and functional well-being through financial well-being remained significant.

CONCLUSIONS

Poor financial well-being attributable to multimorbidity partially mediates the direct impact of chronic conditions on HRQoL in Chinese cancer patients, particularly their physical and functional well-being.

Socioeconomic gradient in mortality of working age and older adults with multiple long-term conditions in England and Ontario, Canada

BACKGROUND

There is currently mixed evidence on the influence of long-term conditions and deprivation on mortality. We aimed to explore whether number of long-term conditions contribute to socioeconomic inequalities in mortality, whether the influence of number of conditions on mortality is consistent across socioeconomic groups and whether these associations vary by working age (18-64 years) and older adults (65 + years). We provide a cross-jurisdiction comparison between England and Ontario, by replicating the analysis using comparable representative datasets.

METHODS

Participants were randomly selected from Clinical Practice Research Datalink in England and health administrative data in Ontario. They were followed from 1 January 2015 to 31 December 2019 or death or deregistration. Number of conditions was counted at baseline. Deprivation was measured according to the participant's area of residence. Cox regression models were used to estimate hazards of mortality by number of conditions, deprivation and their interaction, with adjustment for age and sex and stratified between working age and older adults in England (N = 599,487) and Ontario (N = 594,546).

FINDINGS

There is a deprivation gradient in mortality between those living in the most deprived areas compared to the least deprived areas in England and Ontario. Number of conditions at baseline was associated with increasing mortality. The association was stronger in working age compared with older adults respectively in England (HR = 1.60, 95% CI 1.56,1.64 and HR = 1.26, 95% CI 1.25,1.27) and Ontario (HR = 1.69, 95% CI 1.66,1.72 and HR = 1.39, 95% CI 1.38,1.40). Number of conditions moderated the socioeconomic gradient in mortality: a shallower gradient was seen for persons with more long-term conditions.

CONCLUSIONS

Number of conditions contributes to higher mortality rate and socioeconomic inequalities in mortality in England and Ontario. Current health care systems are fragmented and do not compensate for socioeconomic disadvantages, contributing to poor outcomes particularly for those managing multiple long-term conditions. Further work should identify how health systems can better support patients and clinicians who are working to prevent the development and improve the management of multiple long-term conditions, especially for individuals living in socioeconomically deprived areas.

Multimorbidity and Complexity Among Patients with Cancer in Ontario: A Retrospective Cohort Study Exploring the Clustering of 17 Chronic Conditions with Cancer

BACKGROUND

Multimorbidity is a concern for people living with cancer, as over 90% have at least one other condition. Multimorbidity complicates care coming from multiple providers who work within separate, siloed systems. Information describing high-risk and high-cost disease combinations has potential to improve the experience, outcome, and overall cost of care by informing comprehensive care management frameworks. This study aimed to identify disease combinations among people with cancer and other conditions, and to assess the health burden associated with those combinations to help healthcare providers more effectively prioritize and coordinate care.

METHODS

We used a population-based retrospective cohort design including adults with a cancer diagnosis between March-2003 and April-2013, followed-up until March 2018. We used observed disease combinations defined by level of multimorbidity and partitive (k-means) clusters, ie groupings of similar diseases based on the prevalence of each condition. We assessed disease combination-associated health burden through health service utilization, including emergency department visits, primary care visits and hospital admissions during the follow-up period.

RESULTS

549,248 adults were included in the study. Anxiety, diabetes mellitus, hypertension, and osteoarthritis co-occurred with cancer 1.1 to 5.3 times more often than expected by chance. Disease combinations varied by cancer type and age but were similar between sexes. The largest partitive cluster included cancer and anxiety, with at least 25% of individuals also having osteoarthritis. Cancer also tended to co-occur with hypertension (8.0%) or osteoarthritis (6.2%). There were differences between clusters in healthcare utilization, regardless of the number of disease combinations or clustering approach used.

CONCLUSION

Researchers, clinicians, policymakers, and other stakeholders can use the clustering information presented here to improve the healthcare system for people with cancer multimorbidity by developing cluster-specific care management and clinical guidelines for common disease combinations.

Factors associated with health care utilization and catastrophic health expenditure among cancer patients in China: Evidence from the China health and retirement longitudinal study

Background

Cancer, the leading cause of mortality in China, is a significant burden on patients, their families, the medical system, and society at large. However, there is minimal data on health service utilization and catastrophic health expenditure (CHE) among cancer patients in China. The objective of this study was to identify factors associated with health care utilization and CHE in Chinese cancer patients.

Methods

The 2018 wave of a nationally representative dataset, the China Health and Retirement Longitudinal Study, was used in our study. Of 18,968 respondents recruited for the analysis, 388 were clinically diagnosed with cancer. CHE was defined as household health expenditure that exceeded 40% of non-food household expenses. A binary logistic regression model was used to identify the risks of cancer exposure among all participants, along with the likelihood of CHE in households with cancer patients at the 40% threshold. A negative binomial regression model was used to identify determinants of health service utilization among cancer patients.

Results

Contracting a family physician (incidence rate ratio IRR: 2.38, 1.18-4.77), Urban Employee Basic Medical Insurance (IRR: 4.02, 1.91-8.46, compared to the uninsured), Urban and Rural Resident Basic Medical Insurance (IRR: 3.08, 1.46-6.49, compared to the uninsured), and higher per-capita household consumption were positively associated with inpatient service utilization. Patients with a college education and above reported a greater number of outpatient visits (IRR: 5.78, 2.56-13.02) but fewer inpatient hospital days (IRR: 0.37, 0.20-0.67). Being diagnosed with a non-cancer chronic non-communicable disease was associated with an increased number of outpatient visits (IRR: 1.20, 1.10-1.31). Of the 388 participants, 50.1% of households had CHE, which was negatively correlated with a larger household size (odds ratio OR: 0.52, 0.32-0.86) and lower socioeconomic status [for quintile 5 (lowest group) OR: 0.32, 0.14-0.72].

Conclusions

The socioeconomic characteristics of cancer patients had a considerable impact on their healthcare utilization. Individualized and targeted strategies for cancer management should be implemented to identify high-risk populations and trace the utilization of care among Chinese cancer patients. Strategic purchasing models in cancer care and social health insurance with expanded benefits packages for cancer patients are crucial to tackling the cancer burden in China.

Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics

Multimorbidity is characterized by multidimensional complexity emerging from interactions between multiple diseases across levels of biological (including genetic) and environmental determinants and the complex array of interactions between and within cells, tissues and organ systems. Advances in spatial genomic research have led to an unprecedented expansion in our ability to link alterations in genome folding with changes that are associated with human disease. Studying disease-associated genetic variants in the context of the spatial genome has enabled the discovery of transcriptional regulatory programmes that potentially link dysregulated genes to disease development. However, the approaches that have been used have typically been applied to uncover pathological molecular mechanisms occurring in a specific disease-relevant tissue. These forms of reductionist, targeted investigations are not appropriate for the molecular dissection of multimorbidity that typically involves contributions from multiple tissues. In this perspective, we emphasize the importance of a whole-body understanding of multimorbidity and discuss how spatial genomics, when integrated with additional omic datasets, could provide novel insights into the molecular underpinnings of multimorbidity.

Multimorbidity and Its Associations With Anxiety and Depression Among Newly Diagnosed Patients With Breast Cancer: A Retrospective Observational Cohort Study in a US Commercially Insured and Medicare Advantage Population

Background

Multimorbidity is common in patients with breast cancer, thus increasing the complexity of cancer care and economic burden, worsening their prognosis and quality of life. The prevalence of multimorbidity and its influence on psychological distress among patients with breast cancer have not been well characterized.

Objectives

To examine the prevalence of multimorbidity and its associations with anxiety and depression among newly diagnosed patients with breast cancer.

Methods

We conducted a retrospective observational cohort study using a large administrative claims database. Patients with breast cancer (ICD-10-CM: C50.x) were identified during the study period (1/1/2017-12/31/2020). The index date was defined as the diagnosis date of breast cancer. Demographics and comorbid conditions were assessed using data within 12 months prior to the index date. Multimorbidity was defined as the presence of ≥2 comorbid conditions. Anxiety and depression were examined using data within 12 months after the index date. Multivariable logistic regressions were performed to examine the associations between multimorbidity and anxiety and depression, adjusting for sociodemographic factors.

Results

Of the 6392 patients with newly diagnosed breast cancer, 86.9% had multimorbidity at the time of breast cancer diagnosis. The median number of comorbid conditions was 5. Overall, 27.7% experienced anxiety, and 21.9% experienced depression in the first year following breast cancer diagnosis. An increased number of comorbid conditions was associated with elevated prevalence of both anxiety and depression. After adjusting for possible confounding factors, number of comorbid conditions was significantly associated with risk of anxiety (adjusted odds ratio [95% confidence interval (CI)]: 1.17 [1.15-1.19]), and depression (1.24 [1.21-1.26]); all P < .0001.

Conclusions

Multimorbidity was highly prevalent among patients with breast cancer and was strongly associated with increased risk of anxiety and depression in the first year following breast cancer diagnosis. The presence of multimorbidity, anxiety, and depression should be considered in the context of clinical decision making to optimize cancer care and improve mental health and quality of life.

The role of multimorbidity in short-term mortality of lung cancer patients in Spain: a population-based cohort study

AIM

Chronic diseases often occur simultaneously and tend to be associated with adverse health outcomes, but limited research has been undertaken to understand their role in lung cancer mortality. Therefore, this study aims to describe the prevalence and patterns of having one (comorbidity) or ≥ 2 chronic diseases (multimorbidity) among lung cancer patients in Spain, and to examine the association between comorbidity or multimorbidity and short-term mortality risk at six months after cancer diagnosis.

METHODS

In this population-based cohort study, data were drawn from two Spanish population-based cancer registries, Girona and Granada, and electronic health records. We identified 1259 adult lung cancer patients, diagnosed from 1st January 2011 to 31st December 2012. We identified the most common patterns of individual comorbidities and their pairwise correlations. We used a flexible parametric modelling approach to assess the overall short-term mortality risk 6 months after cancer diagnosis by levels of comorbidity after adjusting for age, sex, smoking status, province of residence, surgery, cancer stage, histology, and body mass index.

RESULTS

We found high prevalence of comorbidity in lung cancer patients, especially among the elderly, men, those diagnosed with advanced-stage tumours, smokers, and obese patients. The most frequent comorbidities were chronic obstructive pulmonary disease (36.6%), diabetes (20.7%) and heart failure (16.8%). The strongest pairwise correlation was the combination of heart failure with renal disease (r = 0.20, p < 0.01), and heart failure with diabetes (r = 0.16, p < 0.01). Patients with either one or two or more comorbidities had 40% higher overall mortality risk than those without comorbidities (aHR for comorbidity: 1.4, 95%CI: 1.1-1.7; aHR for multimorbidity: 1.4, 95%CI: 1.1-1.8), when relevant confounding factors were considered.

CONCLUSIONS

The presence of comorbid diseases, rather than the number of comorbidities, was associated with increasing the risk of short-term lung cancer mortality in Spain. Comorbidity was a consistent and independent predictor of mortality among lung cancer patients, six months after diagnosis. The most common comorbid conditions were age-, obesity- and tobacco-related diseases. Our findings highlight the need to develop targeted preventive interventions and more personalised clinical guidelines to address the needs of lung cancer patients with one or more comorbidities in Spain.