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Integrating Quality of Life and Survival Outcomes in Cardiovascular Clinical Trials.

ABSTRACT: Background Survival and health status (eg, symptoms and quality of life) are key outcomes in clinical trials of heart failure treatment. However, health status can only be recorded on survivors, potentially biasing treatment effect estimates when there is differential survival across treatment groups. Joint modeling of survival and health status can address this bias. Methods and Results We analyzed patient-level data from the PARTNER 1B trial (Placement of Aortic Transcatheter Valves) of transcatheter aortic valve replacement versus standard care. Health status was quantified with the Kansas City Cardiomyopathy Questionnaire (KCCQ) at randomization, 1, 6, and 12 months. We compared hazard ratios for survival and mean differences in KCCQ scores at 12 months using several models: the original growth curve model for KCCQ scores (ignoring death), separate Bayesian models for survival and KCCQ scores, and a Bayesian joint longitudinal-survival model fit to either 12 or 30 months of survival follow-up. The benefit of transcatheter aortic valve replacement on 12-month KCCQ scores was greatest in the joint-model fit to all survival data (mean difference, 33.7 points; 95% credible intervals [CrI], 24.2-42.4), followed by the joint-model fit to 12 months of survival follow-up (32.3 points; 95% CrI, 22.5-41.5), a Bayesian model without integrating death (30.4 points; 95% CrI, 21.4-39.3), and the original growth curve model (26.0 points; 95% CI, 18.7-33.3). At 12 months, the survival benefit of transcatheter aortic valve replacement was also greater in the joint model (hazard ratio, 0.50; 95% CrI, 0.32-0.73) than in the nonjoint Bayesian model (0.54; 95% CrI, 0.37-0.75) or the original Kaplan-Meier estimate (0.55; 95% CI, 0.40-0.74). Conclusions In patients with severe symptomatic aortic stenosis and prohibitive surgical risk, the estimated benefits of transcatheter aortic valve replacement on survival and health status compared with standard care were greater in joint Bayesian models than other approaches.

SUBMITTER: Spertus JV

PROVIDER: S-EPMC6579042 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Integrating Quality of Life and Survival Outcomes in Cardiovascular Clinical Trials.

Spertus Jacob V JV Hatfield Laura A LA Cohen David J DJ Arnold Suzanne V SV Ho Martin M Jones Philip G PG Leon Martin M Zuckerman Bram B Spertus John A JA

Circulation. Cardiovascular quality and outcomes 20190613 6

Background Survival and health status (eg, symptoms and quality of life) are key outcomes in clinical trials of heart failure treatment. However, health status can only be recorded on survivors, potentially biasing treatment effect estimates when there is differential survival across treatment groups. Joint modeling of survival and health status can address this bias. Methods and Results We analyzed patient-level data from the PARTNER 1B trial (Placement of Aortic Transcatheter Valves) of transc ...[more]

PMID: 31189406

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Project description:OBJECTIVE:Poor reporting in randomized clinical trial (RCT) abstracts reduces quality and misinforms readers. Spin, a biased presentation of findings, could frequently mislead clinicians to accept a clinical intervention despite non-significant primary outcome. Therefore, good reporting practices and absence of spin enhances research quality. We aim to assess the reporting quality and spin in abstracts of RCTs evaluating the effect of periodontal therapy on cardiovascular (CVD) outcomes. METHODS:PubMed, Scopus, the Cochrane Central Register of Controlled Trials (CENTRAL), and 17 trial registration platforms were searched. Cohort, non-randomized, non-English studies, and pediatric studies were excluded. RCT abstracts were reviewed by 2 authors using the CONSORT for abstracts and spin checklists for data extraction. Cohen's Kappa statistic was used to assess inter-rater agreement. Data on the selected RCT publication metrics were collected. Descriptive analysis was performed with non-parametric methods. Correlation analysis between quality, spin and bibliometric parameters was conducted. RESULTS:24 RCTs were selected for CONSORT analysis and 14 fulfilled the criteria for spin analysis. Several important RCT elements per CONSORT were neglected in the abstract including description of the study population (100%), explicitly stated primary outcome (87%), methods of randomization and blinding (100%), trial registration (87%). No RCT examined true outcomes (CVD events). A significant fraction of the abstracts appeared with at least one form of spin in the results and conclusions (86%) and claimed some treatment benefit in spite of non-significant primary outcome (64%). High-quality reporting had a significant positive correlation with reporting of trial registration (p = 0.04) and funding (p = 0.009). Spinning showed marginal negative correlation with reporting quality (p = 0.059). CONCLUSION:Poor adherence to the CONSORT guidelines and high levels of data spin were found in abstracts of RCTs exploring the effects of periodontal therapy on CVD outcomes. Our findings indicate that journal editors and reviewers should consider strict adherence to proper reporting guidelines to improve reporting quality and reduce waste.

Project description:Importance:Quality of life (QoL) is an important consideration in cancer medicine, especially because drugs are becoming more costly and may only result in modest gains in overall survival. However, there has been no descriptive analysis for the points at which QoL is measured in cancer trials. Objective:To estimate the prevalence of studies that measure QoL at different points and see how many studies measure QoL for the entirety of a patient's life. Design, Setting, and Participants:This cross-sectional analysis includes all articles on oncology clinical trials in the 3 highest-impact oncology journals, published between July 2015 and June 2018, that reported QoL outcomes. Main Outcomes and Measures:Data were abstracted on when QoL was assessed and the characteristics of these studies. Results:For all 149 studies that met inclusion criteria, QoL assessment was high during treatment (104 articles [69.8%]), during follow-up (81 articles [54.4%]), and after the end of the intervention (68 articles [45.6%]). In 5 of the 149 studies (3.4%), QoL was assessed until death, including in only 1 of the 74 studies on metastatic or incurable cancers. Among these 5 studies, only 1 (20%) used a drug intervention, 1 (20%) used a behavioral intervention, and 2 (40%) used a radiation intervention; only 1 of 5 was in the metastatic setting. The number of studies that reported a positive QoL outcome (ie, QoL outcome was more favorable in the intervention group than in the control group) was between 42 of 81 articles (51.9%) and 16 of 28 articles (57.1%) for most QoL assessment points but only 1 of 5 articles (20%) for studies measuring QoL until death. Conclusions and Relevance:This study found that most clinical trials assessed QoL during the treatment or intervention and often during a given amount of follow-up but infrequently assessed QoL on disease progression and rarely followed QoL until the end of the patient's life. Most studies reporting QoL until the end of life reported worse QoL outcomes for the intervention group than the control group. Future research and policy recommendations should consider not just short-term QoL outcomes but QoL outcomes throughout the patient's cancer care.

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Integrating Quality of Life and Survival Outcomes in Cardiovascular Clinical Trials.

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Integrating Quality of Life and Survival Outcomes in Cardiovascular Clinical Trials.

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