Health-related quality of life in lung cancer survivors: Latent class and latent transition analysis

Latent profile analysis for assessing symptom clusters in women with breast cancer

PURPOSE

To identify symptom clusters among breast cancer survivors and investigate differences in health-related quality of life (HRQoL) and distress based on these discerned symptom clusters using latent profile analysis.

METHODS

We enrolled 655 adult breast cancer survivors aged 19 years and older, registered with the Cancer Survivor Integrated Supportive Center from May 2020 to July 2022. The study measured five symptoms-pain, fatigue, insomnia, anxiety, and depression-using a Visual Analogue Scale ranging from 0 to 10 points. Distress was measured using the National Comprehensive Cancer Network Distress Thermometer, with scores ranging from 0 to 10 points. HRQoL was determined using the EuroQol-5 Dimension questionnaire. Data analysis was conducted using the Jamovi and Mplus 8.8 software programs.

RESULTS

The Cluster with Few Symptoms (46.8%) was the most common, whereas the Psychological Cluster with a very high degree of depression and anxiety accounted for 20.0%, and the Moderate symptom cluster with symptoms of 3 or more points accounted for 14.4%. Distress scores were relatively high in the Psychological Cluster and the Pain-Fatigue-Insomnia Cluster, and were lowest in the Cluster with Few Symptoms (F = 103.92, p < 0.001). HRQoL scores were highest in the Cluster with Few Symptoms and lowest in the Pain-Fatigue-Insomnia Cluster (F = 177.62, p < 0.001).

CONCLUSIONS

Approximately half of breast cancer survivors who had completed the major treatment experienced persistent high symptoms such as depression and anxiety or pain, fatigue, and insomnia.

IMPLICATIONS FOR CANCER SURVIVORS

These findings provide foundational data for developing tailored intervention strategies and programs based on symptom experiences.

Associations of frailty with symptoms, and HRQOL in older cancer survivors after cancer treatments: a systematic review and meta-analyses

PURPOSE

Frailty in older adult cancer survivors after cancer treatments is associated with various health outcomes. However, there is less agreement on how frailty affects symptoms and health-related quality of life (HRQOL). This systematic review and meta-analysis aimed to evaluate the current literature on frailty, symptoms, and HRQOL, as well as the associations of frailty with these factors in older adult cancer survivors with chemotherapy.

METHODS

A review was conducted on peer-reviewed publications from 2008 to 2023, using seven electronic databases. Meta-analyses were performed using random effects models to determine pooled effect estimates for frailty prevalence, symptom severity, and HRQOL scores.

RESULTS

A total of 26 studies involving older cancer survivors were included in the analysis. Most of these studies were conducted in Western countries and focused on White survivors, particularly those with breast cancer. The mean pooled prevalence of frailty was 43.5%. Among frail survivors, the most common symptoms reported after cancer treatments were pain (36.4%), neuropathy (34.1%), and fatigue (21.3%). Frailty was associated with higher pooled mean symptom severity (B = 1.23, p = 0.046) and lower functional HRQOL (B = - 0.31, p = 0.051, with marginal significance) after cancer treatments.

CONCLUSION

Frail older cancer survivors are at high risk of adverse symptoms and poor HRQOL after cancer treatment. Further research on screening for frailty is needed to prevent older adults from developing worse symptoms burden and maintain HRQOL. It is also essential to understand the mechanisms of the associations between frailty, symptoms and HRQOL in this population.

Assessing health-related quality of life among cancer survivors during systemic and radiation therapy in Bangladesh: a cancer-specific exploration

BACKGROUND

Evaluating the effects of cancer diagnosis and treatment on a patient's overall well-being is crucial and health-related quality of life (HRQoL) is a reliable metric for assessing this impact. Little is known about HRQoL among cancer survivors across various stages and treatments. The study examined individual and clinical factors influencing HRQoL among cancer survivors.

METHODS

A cross-sectional study was conducted in two specialised cancer care hospitals in Dhaka, Bangladesh. Cancer-diagnosed adults receiving treatment at selected hospitals from January to May 2022 were enrolled. The 5-level EuroQol-5 Dimensions version (EQ-5D-5L) instrument was used to collect HRQoL data. HRQoL scores were derived using UK value sets. The investigation used a multivariable Tobit regression model to determine the association between independent variables and HRQoL scores.

RESULTS

A total of 607 adult patients were enrolled, with 55% being females and 66% aged 36 to 64 years. Reported health problems in five EQ-5D domains include mobility (11%), self-care (11%), usual daily activities (19%), pain/discomfort (21%), and anxiety/depression (46%). Patients with throat, brain, lung, blood, and liver cancer had lower utility scores. Advanced-stage cancer survivors had lower utility scores (β = -49 units, 95% codfidence interval [CI]: -0.75 to -0.22) compared to early-stage survivors. Physically inactive survivors had lower utility scores by 0.41 units (95% CI: -0.51 to -0.30) compared to their counterparts. Private hospital patients had higher utility scores, whereas patients belonged to poor socioeconomic groups scored worse than wealthier ones.

CONCLUSIONS

This study highlights the impact of clinical and individual characteristics on HRQoL among cancer survivors. These findings advocate for an enhanced Bangladeshi cancer patient care model through timely interventions or programs, early detection or diagnosis, tailored treatments, and the promotion of physical activity to bolster HRQoL outcomes.

Predictors of preparedness for recovery following colorectal cancer surgery: a latent class trajectory analysis

AIM

With an interest in providing knowledge for person-centred care, our overall goal is to contribute a greater understanding of diversity among patients in terms of their preparedness before and up to six months after colorectal cancer surgery. Our aim was to describe and provide a tentative explanation for differences in preparedness trajectory profiles.

MATERIAL AND METHODS

The study was explorative and used prospective longitudinal data from a previously published intervention study evaluating person-centred information and communication. The project was conducted at three hospitals in Sweden. Patient-reported outcomes measures, including the Longitudinal Preparedness for Colorectal Cancer Surgery Questionnaire, were collected before surgery, at discharge, and four to six weeks, three months, and six months after surgery. Clinical data were retrospectively obtained from patients' medical records. We used latent class growth models (LCGMs) to identify latent classes that distinguish subgroups of patients who represent different preparedness trajectory profiles. To determine the most plausible number of latent classes, we considered statistical information about model fit and clinical practice relevance. We used multivariable regression models to identify variables that explain the latent classes.

RESULTS

The sample (N = 488) comprised people with a mean age of 68 years (SD = 11) of which 44% were women. Regarding diagnoses, 60% had colon cancer and 40% rectal cancer. The LCGMs identified six latent classes with different preparedness for surgery and recovery trajectories. The latent classes were predominantly explained by differences in age, sex, physical classification based on comorbidities, treatment hospital, global health status, distress, and sense of coherence (comprehensibility and meaningfulness).

CONCLUSION

Contrary to the received view that emphasizes standardized care practices, our results point to the need for adding person-centred and tailored approaches that consider individual differences in how patients are prepared before and during the recovery period related to colorectal cancer surgery.

Health-related quality of life profiles in adolescents and young adults with chronic conditions

PURPOSE

To assess health-related quality of life (HRQOL) among adolescents and young adults (AYAs) with chronic conditions.

METHODS

AYAs (N = 872) aged 14-20 years completed NIH's Patient-Reported Outcomes Measurement Information System® (PROMIS®) measures of physical function, pain interference, fatigue, social health, depression, anxiety, and anger. Latent profile analysis (LPA) was used to group AYAs into HRQOL profiles using PROMIS T-scores. The optimal number of profiles was determined by model fit statistics, likelihood ratio test, and entropy. Multinomial logistic regression models were used to examine how LPA's HRQOL profile membership was associated with patient demographic and chronic conditions. The model prediction accuracy on profile membership was evaluated using Huberty's I index with a threshold of 0.35 for good effect.

RESULTS

A 4-profile LPA model was selected. A total of 161 (18.5%), 256 (29.4%), 364 (41.7%), and 91 (10.4%) AYAs were classified into Minimal, Mild, Moderate, and Severe HRQOL Impact profiles. AYAs in each profile had distinctive mean scores with over a half standard deviation (5-points in PROMIS T-scores) of difference between profiles across most HRQOL domains. AYAs who were female or had conditions such as mental health condition, hypertension, and self-reported chronic pain were more likely to be in the Severe HRQOL Impact profile. The Huberty's I index was 0.36.

CONCLUSIONS

Approximately half of AYAs with a chronic condition experience moderate to severe HRQOL impact. The availability of risk prediction models for HRQOL impact will help to identify AYAs who are in greatest need of closer clinical care follow-up.

Latent profile analysis for quality of life in older patients

Background

Quality of life (QOL) is a complex concept known for being influenced by socio-demographic characteristics, individual needs, perceptions and expectations. The study investigates influences of such heterogeneous variables and aims to identify and describe subgroups of older patients who share similar response patterns for the four domains (physical health, psychological health, social relationships and environment) of World Health Organization Quality of Life instrument, Short Form (WHOQOL-BREF).

Methods

The sample used included older Romanian patients (N = 60; equal numbers of men and women; mean age was 71.95, SD = 5.98). Latent Profile Analysis (LPA) was conducted to explore quality of life profiles with the four WHOQOL-BREF domains as input variables. Differences between profiles were analysed by MANOVA and ANOVAs as a follow-up.

Results

The LPA results showed that the three-profile model was the most suitable and supported the existence of three distinct QOL profiles: low and very low (28.3%), moderate (63.3%) and high (8.4%). The relative entropy value was high (0.86), results pointed to a good profile solution and the three profiles differed significantly from one another.

Conclusion

Our results reveal heterogeneity within the older adult sample and provide meaningful information to better tailor QOL improvement programs to the needs of older patient groups, especially those designed for patients of profiles related to poorer QOL in different domains.

Applying the thresholds for clinical importance for fourteen key domains of the EORTC QLQ-C30: a latent class analysis of cancer survivors

A person’s quality of life is impacted from the beginning of their oncology experience. One of the most common tools to measure quality of life is the EORTC QLQ-C30. The absolute scores it produces can be difficult to interpret in the clinical setting, and thresholds to help identify those who require intervention have recently been introduced. The aim of this research was to identify heterogeneity of these thresholds for clinical importance using latent class analysis in cancer survivors (those undergoing and those who have completed treatment) attending a hospital in the northwest of Ireland. We identified 3 distinct classes of cancer survivors, using Mplus 6.11: high clinical impact (13.9%), compromised physical function (40.3%) and low clinical impact (45.9%). The compromised physical function group were slightly more likely to be older (OR = 1.042, p < .05, CI = 1.000–1.086), not employed (OR = 8.347, p < .01, CI = 2.092–33.305), have lower PG-SGA scores (OR = .826, p < .001, CI = .755–.904), and not have been diagnosed in the last 2 years (OR = .325, p < .05, CI = .114–.923) compared to the high clinical impact group. The low clinical impact group were more likely to be female (OR = 3.288, p < .05, CI = 1.281–1.073), not employed (OR = 10.129, p < .01, CI = 2.572–39.882), have a lower BMI (OR = .921, p < .05, CI = .853–.994), and lower PG-SGA scores (OR = .656, p < .001, CI = .573–.750) than the high clinical impact group. Functional and symptom issues impact on quality of life, and therefore, identifying those of clinical importance is crucial for developing supportive care strategies.

Heterogeneity in Quality of Life of Long-Term Colon Cancer Survivors: A Latent Class Analysis of the Population-Based PROFILES Registry

Background

Long‐term colon cancer survivors present heterogeneous health‐related quality of life (HRQOL) outcomes. We determined unobserved subgroups (classes) of survivors with similar HRQOL patterns and investigated their stability over time and the association of clinical covariates with these classes.

Materials and Methods

Data from the population‐based PROFILES registry were used. Included were survivors with nonmetastatic (TNM stage I–III) colon cancer (n = 1,489). HRQOL was assessed with the Dutch translation of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 version 3.0. Based on survivors’ HRQOL, latent class analysis (LCA) was used to identify unobserved classes of survivors. Moreover, latent transition analysis (LTA) was used to investigate changes in class membership over time. Furthermore, the effect of covariates on class membership was assessed using multinomial logistic regression.

Results

LCA identified five classes at baseline: class 1, excellent HRQOL (n = 555, 37.3%); class 2, good HRQOL with prevalence of insomnia (n = 464, 31.2%); class 3, moderate HRQOL with prevalence of fatigue (n = 213, 14.3%); class 4, good HRQOL with physical limitations (n = 134, 9.0%); and class 5, poor HRQOL (n = 123, 8.3%). All classes were stable with high self‐transition probabilities. Longer time since the diagnosis, no comorbid conditions, and male sex were associated with class 1, whereas older age was associated with class 4. Clinical covariates were not associated with class membership.

Conclusion

The identified classes are characterized by distinct patterns of HRQOL and can support patient‐centered care. LCA and LTA are powerful tools for investigating HRQOL in cancer survivors.

Implications for Practice

Long‐term colon cancer survivors show great heterogeneity in their health‐related quality of life. This study identified five distinct clusters of survivors with similar patterns of health‐related quality of life and showed that these clusters remain stable over time. It was also shown that these clusters do not significantly differ in tumor characteristics or received treatment. Cluster membership of long‐term survivors can be identified by sociodemographic characteristics but is not predetermined by diagnosis and treatment.

Health‐related quality of life is well studied, but most studies have investigated only specific aspects of quality of life despite the vast heterogeneity of adverse effects experienced. This article focuses on heterogeneity and stability in health‐related quality of life for a cohort of long‐term survivors of colon cancer.

Health-Related Quality of Life Declines Over 3 Years for Congenital Heart Disease Survivors

BACKGROUND

Because of medical advancements, many congenital heart disease (CHD) survivors are relatively symptom-free until adulthood, at which time complications may occur. Worsening health status likely drives a change in patient-reported outcomes, such as health-related quality of life (HRQoL), although change in HRQoL has not been investigated among adolescent and young adult CHD survivors.

OBJECTIVE

The aims of the current mixed cross-sectional and longitudinal study were to (1) examine changes in HRQoL over 3 years and (2) identify any demographic (age, sex, estimated family income, and distance from medical center) and medical predictors (functional status and number of cardiac-related medications) of that change.

METHODS

Baseline and 3-year follow-up data were obtained via an online survey of 172 CHD survivors (15-39 years old at baseline; 25% simple, 45% moderate, 30% complex) recruited from a pediatric hospital and an adult hospital. Medical predictors were abstracted from electronic medical records.

RESULTS

After controlling for New York Heart Association functional class, mixed-effects models identified significant declines in all subscales of the Research and Development Corporation 36-Item Health Survey 1.0 across the 3-year timeframe. A lower estimated family income (≤$35 000) predicted more decline in physical functioning (b = 0.5, 95% confidence interval, 0.2-0.8; P = .001) and emotional functioning (b = 0.3, 95% confidence interval, 0.1-0.5; P = .017). No other significant demographic or medical predictors were identified.

CONCLUSIONS

Study findings highlight the importance of tracking patient-reported outcomes over time, suggesting that medical staff should discuss HRQoL with CHD survivors during late adolescence and early adulthood before decline.

Patterns of substance use before and after hospitalization among patients seen by an inpatient addiction consult service: A latent transition analysis

BACKGROUND AND AIMS

Polysubstance use is common and contributes to morbidity and mortality of hospitalized patients, and yet little is known about patterns of substance use among hospitalized patients, or how an addiction consult service (ACS) might impact polysubstance use after discharge. The objective of this study was to identify patterns of substance use at admission and after discharge among hospitalized patients with substance use disorders who saw an ACS.

DESIGN

Prospective cohort study. We used latent transition analysis of substance use scores at the time of hospital admission and 30 to 90 days posthospitalization.

SETTING

Single, academic health center with an ACS in Portland, Oregon, from 2015 to 2018.

PARTICIPANTS/CASES

Patients were eligible if they received a consult to the inpatient ACS.

MEASUREMENTS

We used Addiction Severity Index-Lite scores to capture self-reported substance use at baseline and follow-up for heroin, other opioid, alcohol, amphetamine, and cocaine.

FINDINGS

From 2015 to 2018, 486 individuals consented to participate. More than half of patients used more than one substance at baseline. Of those reporting any baseline opioid use, nearly three-quarters (n=187, 69.5%) had polysubstance use in the previous 30 days, including alcohol (n=80, 29.7%), cocaine (n=25, 9.3%), or amphetamine use (n=142, 52.8%). We identified three patterns of substance use at baseline: 1) alcohol use dominant, 2) polysubstance use dominant, and 3) heroin and other opioid use dominant. Patients transitioned along five trajectories to three different follow-up profiles that showed lower endorsement of all substances used. Slightly more than 40% (40.1%) of patients newly endorsed abstinence of at least one substance at follow-up.

CONCLUSIONS

Polysubstance use is common in hospitalized patients with substance use disorders and identifying patterns of polysubstance use can guide clinical management. Hospital providers should prepare to manage polysubstance use during hospitalization and hospitals should broaden care beyond interventions for opioid use disorder.

A non-compensatory analysis of quality of life in breast cancer survivors using multivariate hidden Markov modeling

PURPOSE

Health-related quality of life (HRQoL) is a multidimensional concept comprising multiple domains such as physical, emotional, and social well-being. Many analyses use a sum score to represent the construct. However, this approach implies that gain in one domain can compensate for a deficit in another, and thus such analyses may not capture HRQoL profiles. Additionally, within-individual change over time, such as improvement in one domain but deterioration in another, may not be detected. The objectives of this research are to demonstrate the utility of a non-compensatory approach by (1) evaluating this approach applied to HRQoL data, and (2) comparing the approach to a compensatory method.

METHODS

Data from a sample of 653 breast cancer survivors (BCS) provided five measurement time points over 18 months. We analyzed the scores from five domains on the FACT-B questionnaire (physical, functional, social, and emotional well-being and breast cancer-related concerns) using the multivariate hidden Markov model (MHMM), a non-compensatory approach that identifies different HRQoL states and associated BCS subgroups and their trajectories.

RESULTS

The MHMM delineated six states. States 1 and 2 had low well-being scores across all domains, with state 2 slightly better than state 1. States 3 and 4 had similar overall HRQoL scores, but different profiles with compensation occurring across the domains of both physical and social well-being. States 5 and 6 had almost identical overall scores with compensation occurring between the domains of both social and emotional well-being. Over time, states 3-6 mostly "communicated" with each other (with moderate probabilities of transitioning between states). Compensation across domains could mask subtle changes occurring in BCS. We found that a trend analysis using both compensatory and non-compensatory approaches showed improvement in the HRQoL in BCS over time.

CONCLUSION

The non-compensatory analysis of FACT-B shows differential profiles and trajectories in the HRQoL of BCS not captured by the sum score or one-domain-at-a-time approach.

Post-traumatic growth and related factors among 1221 Chinese cancer survivors

OBJECTIVE

There is an increasing number of studies on the post-traumatic growth (PTG) of cancer survivors worldwide. However, few Chinese studies have reported about PTG in cancer survivors because of the underdevelopment of community health services. This study aimed to evaluate the level of PTG in China and explore related factors among a large sample of survivors of more than 12 cancer types.

METHODS

We recruited 1236 survivors from 14 sites of the Beijing Cancer Rehabilitation Association. Survivors completed standardized questionnaires assessing PTG, social support, coping styles, demographic characteristics, and clinical conditions. Multivariate linear regression was used to evaluate potential predictive factors of PTG.

RESULTS

A total of 1221 (98.7%) subjects completed the questionnaires. The average PTG score was 61.15 ± 20.26. Seven variables were included in the final regression model: social support, coping style, time after treatment, exercise, BMI, work status, and economic income (P < .05). Survivors who had low levels of social support, had negative coping strategies, had a time after treatment of less than 5 years, exercised irregularly, had an abnormal BMI, were unemployed, or had low economic income had lower PTG levels.

CONCLUSIONS

PTG levels among Chinese cancer survivors are associated with social support, coping style, time after treatment, exercise, BMI, work status, and economic income. Strategies tailored to Chinese survivors should be developed to promote their PTG and improve their physical and psychological well-being.

Differential risk group of developing stroke among older women with gouty arthritis: A latent transition analysis

OBJECTIVE

Gout-related comorbidities are intricate and its clinical features may demonstrate sex difference; however, few studies have evaluated the links between comorbidities and gout in a female population. The objectives of this study were to compare the aggregation and transitive trajectories of comorbidities of gout, and their consequences in female and male gout populations.

METHODS

A prospective cohort study was conducted using data from the Taiwan National Health Insurance Research Database. A female and male gout population were followed up from 2000 to 2009 to identify the comorbidities of cardiovascular disease, hyperlipidemia, hypertension, diabetes mellitus (DM) and chronic kidney disease. The cumulative incidence of stroke from 2000 to 2010 was examined. A latent trajectory analysis was used to determine the transitive trajectories of the comorbidities of gout.

RESULTS

Both female and male patients with gout had five risk cluster transition (CT) phenotypes of comorbidities within 10-year follow-up: CT1 and CT2, with various persistent comorbidities; CT3, with few persistent comorbidities; and CT4 and CT5, with transfer to cluster 1 from other clusters. The female participants in CT2 predominantly experienced DM and were associated with significantly increased risk of developing stroke.

CONCLUSION

Diabetes is a notable risk factor for the development of stroke in female patients with gout. Early assessment and management for the comorbidities of gout, particularly in DM, would effectively reduce future stroke risk in female gout population.

Health-Related Quality of Life Among Homeless Smokers: Risk and Protective Factors of Latent Class Membership

Health-related quality of life (HRQoL) is a multidimensional assessment of well-being and health status. Most work in this area assumes that HRQoL is a homogenous construct; however, it is possible HRQoL subgroups may exist. The purpose of the study was to characterize common classes of HRQoL among adult, homeless smokers, a particularly vulnerable group of the larger population, and to evaluate risk and protective factors of HRQoL class membership. Homeless smokers (N = 456; 65.1% male; M_age = 43.19 years [SD = 11.77]) completed self-report measures of sociodemographics, smoking characteristics, anxiety sensitivity, stress, social support, and the Center for Disease Control (CDC) four-item HRQoL measure. A latent class analysis was conducted for HRQoL. Multinomial regression models were used to simultaneously test correlates of class membership. A three-class solution, consisting of poor HRQoL, moderate HRQoL, and excellent HRQoL, demonstrated superior fit. Correlates of class membership included sex, age, lifetime months of being homeless, smoking characteristics, anxiety sensitivity, stress, and social support. The current findings provide novel evidence for three distinct classes of HRQoL among homeless smokers. Results suggest that older smokers with greater emotional distress, as evidenced by greater anxiety sensitivity, greater stress, and less social support, may be particularly vulnerable to poorer HRQoL.

Longitudinal Model Building Using Latent Transition Analysis: An Example Using School Bullying Data

Applications of latent transition analysis (LTA) have emerged since the early 1990s, with numerous scientific findings being published in many areas, including social and behavioral sciences, education, and public health. Although LTA is effective as a statistical analytic tool for a person-centered model using longitudinal data, model building in LTA has often been subjective and confusing for applied researchers. To fill this gap in the literature, we review the components of LTA, recommend a framework of fitting LTA, and summarize what acceptable model evaluation tools should be used in practice. The proposed framework of fitting LTA consists of six steps depicted in Figure 1 from step 0 (exploring data) to step 5 (fitting distal variables). We also illustrate the framework of fitting LTA with data on concerns about school bullying from a sample of 1,180 students ranging from 5th to 9th grade (mean age = 12.2 years, SD = 1.29 years at Time 1) over three semesters. We identified four groups of students with distinct patterns of bullying concerns, and found that their concerns about bullying decreased and narrowed to specific concerns about rumors, gossip, and social exclusion over time. The data and command (syntax) files needed for reproducing the results using SAS PROC LCA and PROC LTA (Version 1.3.2) (2015) and Mplus 7.4 (Muthén and Muthén, 1998–2015) are provided as online supplementary materials.

Marfan Syndrome and Quality of Life in the GenTAC Registry

BACKGROUND

Previous small studies suggested reduced quality of life (QOL) for people with Marfan syndrome (MFS) compared with those without MFS. The national registry of GenTAC (Genetically Triggered Thoracic Aortic Aneurysms and Cardiovascular Conditions) is a longitudinal observational cohort study of patients with conditions that predispose to thoracic aortic aneurysms and dissections, including MFS. At the time of registry enrollment, GenTAC study participants are asked to complete questionnaires about demographics, medical history, health habits, and QOL.

OBJECTIVES

This study assessed QOL in GenTAC participants with MFS and identify associated factors using self-reported data.

METHODS

QOL was assessed using the 4 subscales of the Physical Component Summary (PCS) of the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36): physical functioning; role limitations due to physical health; bodily pain; and general health. We studied the association of QOL with self-reported demographics, health behaviors, physical impairments, surgeries, comorbid medical conditions, medications, and MFS severity.

RESULTS

In the GenTAC registry, 389 adults with MFS completed the SF-36. Mean age was 41 years, 51% were men, 92% were white, and 65% were college graduates. The mean PCS composite score was 42.3. In bivariate analysis, predictors of better QOL included college education, marital status, higher household income, private health insurance, full-time employment, moderate alcohol use, fewer prior surgeries, fewer comorbid conditions, absence of depression, and less severe MFS manifestations. In a multivariable analysis, insurance status and employment remained significant predictors of QOL.

CONCLUSIONS

In a large cohort of patients with MFS in the GenTAC registry, health-related QOL was below the population norm. Better QOL was independently associated with socioeconomic factors, not factors related to general health or MFS severity.

Examining health-related quality of life patterns in women with breast cancer

PURPOSE

We aimed to identify subgroups of women with breast cancer who experience different health-related quality of life (HRQOL) patterns during active treatment and survivorship and determine characteristics associated with subgroup membership.

METHODS

We used data from the third phase of the population-based Carolina Breast Cancer Study and included 2142 women diagnosed with breast cancer from 2008 to 2013. HRQOL was measured, on average, 5 and 25 months post diagnosis. Latent profile analysis was used to identify HRQOL latent profiles (LPs) at each time point. Latent transition analysis was used to determine probabilities of women transitioning profiles from 5 to 25 months. Multinomial logit models estimated adjusted odds ratios (aORs) and 95% confidence intervals for associations between patient characteristics and LP membership at each time point.

RESULTS

We identified four HRQOL LPs at 5 and 25 months. LP1 had the poorest HRQOL and LP4 the best. Membership in the poorest profile at 5 months was associated with younger age aOR 0.95; 0.93-0.96, White race aOR 1.48; 1.25-1.65, being unmarried aOR 1.50; 1.28-1.65 and having public aOR 3.09; 1.96-4.83 or no insurance aOR 6.51; 2.12-20.10. At 25 months, Black race aOR 1.75; 1.18-1.82 was associated with the poorest profile membership. Black race and smoking were predictors of deteriorating to a worse profile from 5 to 25 months.

CONCLUSIONS

Our results suggest patient-level characteristics including age at diagnosis and race may identify women at risk for experiencing poor HRQOL patterns. If women are identified and offered targeted HRQOL support, we may see improvements in long-term HRQOL and better breast cancer outcomes.

Prediagnostic serum glucose and lipids in relation to survival in breast cancer patients: a competing risk analysis

Background

Abnormal glucose and lipids levels may impact survival after breast cancer (BC) diagnosis, but their association to other causes of mortality such as cardiovascular (CV) disease may result in a competing risk problem.

Methods

We assessed serum glucose, triglycerides (TG) and total cholesterol (TC) measured prospectively 3 months to 3 years before diagnosis in 1798 Swedish women diagnosed with any type of BC between 1985 and 1999. In addition to using Cox regression, we employed latent class proportional hazards models to capture any heterogeneity of associations between these markers and BC death. The latter method was extended to include the primary outcome (BC death) and competing outcomes (CV death and death from other causes), allowing latent class-specific hazard estimation for cause-specific deaths.

Results

A lack of association between prediagnostic glucose, TG or TC with BC death was observed with Cox regression. With latent class proportional hazards model, two latent classes (Class I and II) were suggested. Class I, comprising the majority (81.5 %) of BC patients, had an increased risk of BC death following higher TG levels (HR: 1.87, 95 % CI: 1.01–3.45 for every log TG increase). Lower overall survival was observed in Class II, but no association for BC death was found. On the other hand, TC positively corresponded to CV death in Class II, and similarly, glucose to death from other causes.

Conclusion

Addressing cohort heterogeneity in relation to BC survival is important in understanding the relationship between metabolic markers and cause-specific death in presence of competing outcomes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1928-z) contains supplementary material, which is available to authorized users.