Does change in health-related quality of life score predict survival? Analysis of EORTC 08975 lung cancer trial

Background:Little is known about whether changes in health-related quality of life (HRQoL) scores from baseline during treatment also predict survival, which we aim to investigate in this study.Methods:We analysed data from 391 advanced non-small-cell lung cancer (NSCLC) patients enrolled in the EORTC 08975 study, which compared palliative chemotherapy regimens. HRQoL was assessed at baseline and after each chemotherapy cycle using the EORTC QLQ-C30 and QLQ-LC13. The prognostic significance of HRQoL scores at baseline and their changes over time was assessed with Cox regression, after adjusting for clinical and socio-demographic variables.Results:After controlling for covariates, every 10-point increase in baseline pain and dysphagia was associated with 11% and 12% increased risk of death with hazard ratios (HRs) of 1.11 and 1.12, respectively. Every 10-point improvement of physical function at baseline (HR=0.93) was associated with 7% lower risk of death. Every 10-point increase in pain (HR=1.08) was associated with 8% increased risk of death at cycle 1. Every 10-point increase in social function (HR=0.91) at cycle 2 was associated with 9% lower risk of death.Conclusions:Our findings suggest that changes in HRQoL scores from baseline during treatment, as measured on subscales of the EORTC QLQ-C30 and QLQ-LC13, are significant prognostic factors for survival

Clinical Outcomes Before and After Complete Everolimus-Eluting Bioresorbable Scaffold Resorption

Background: The Absorb everolimus-eluting bioresorbable vascular scaffold (BVS) provides early drug delivery and mechanical support similar to those of metallic drug-eluting stents, followed by complete resorption in ≈3 years with recovery of vascular structure and function. The ABSORB III trial demonstrated noninferior rates of target lesion failure (cardiac death, target vessel myocardial infarction, or ischemia-driven target lesion revascularization) at 1 year with BVS compared with cobalt chromium everolimus-eluting stents. Between 1 and 3 years and cumulative to 3 years, adverse event rates (particularly target vessel myocardial infarction and scaffold thrombosis) were increased after BVS. We sought to assess clinical outcomes after BVS through 5 years, including beyond the 3-year time point of complete scaffold resorption. Methods: Clinical outcomes from ABSORB III were analyzed by randomized device (intention to treat) cumulative to 5 years and between 3 and 5 years. Results: Rates of target lesion failure, target vessel myocardial infarction, and scaffold thrombosis were increased through the 5-year follow-up with BVS compared with everolimus-eluting stents. However, between 3 and 5 years, reductions in the relative hazards of the BVS compared with everolimus-eluting stents were observed, particularly for target lesion failure (hazard ratio, 0.83 [95% CI, 0.55–1.24] versus 1.35 [95% CI, 1.02–1.78]; P int =0.052) and scaffold thrombosis (hazard ratio, 0.26 [95% CI, 0.02–2.87] versus 3.23 [95% CI, 1.25–8.30]; P int =0.056) compared with the 0- to 3-year time period. Conclusions: In the ABSORB III trial, cumulative 5-year adverse event rates were increased after BVS compared with everolimus-eluting stents. However, the period of excess risk for BVS ended at 3 years, coincident with complete scaffold resorption. Clinical Trial Registration: URL: https://clinicaltrials.gov . Unique identifier: NCT01751906. </jats:sec

Joint models for longitudinal and time-to-event data: a review of reporting quality with a view to meta-analysis

Background Joint models for longitudinal and time-to-event data are commonly used to simultaneously analyse correlated data in single study cases. Synthesis of evidence from multiple studies using meta-analysis is a natural next step but its feasibility depends heavily on the standard of reporting of joint models in the medical literature. During this review we aim to assess the current standard of reporting of joint models applied in the literature, and to determine whether current reporting standards would allow or hinder future aggregate data meta-analyses of model results. Methods We undertook a literature review of non-methodological studies that involved joint modelling of longitudinal and time-to-event medical data. Study characteristics were extracted and an assessment of whether separate meta-analyses for longitudinal, time-to-event and association parameters were possible was made. Results The 65 studies identified used a wide range of joint modelling methods in a selection of software. Identified studies concerned a variety of disease areas. The majority of studies reported adequate information to conduct a meta-analysis (67.7% for longitudinal parameter aggregate data meta-analysis, 69.2% for time-to-event parameter aggregate data meta-analysis, 76.9% for association parameter aggregate data meta-analysis). In some cases model structure was difficult to ascertain from the published reports. Conclusions Whilst extraction of sufficient information to permit meta-analyses was possible in a majority of cases, the standard of reporting of joint models should be maintained and improved. Recommendations for future practice include clear statement of model structure, of values of estimated parameters, of software used and of statistical methods applied

Determining clinically important differences in health-related quality of life in older patients with cancer undergoing chemotherapy or surgery

PURPOSE: Using the EORTC Global Health Status (GHS) scale, we aimed to determine minimal clinically important differences (MCID) in health-related quality of life (HRQOL) changes for older cancer patients with a geriatric risk profile, as defined by the geriatric 8 (G8) health screening tool, undergoing treatment. Simultaneously, we assessed baseline patient characteristics prognostic for HRQOL changes. METHODS: Our analysis included 1424 (G8 ≤ 14) older patients with cancer scheduled to receive chemotherapy (n = 683) or surgery (n = 741). Anchor-based methods, linking the GHS score to clinical indicators, were used to determine MCID between baseline and follow-up at 3 months. A threshold of 0.2 standard deviation (SD) was used to exclude MCID estimates too small for interpretation. Logistic regressions analysed baseline patient characteristics prognostic for HRQOL changes. RESULTS: The 15-item Geriatric Depression Scale (GDS15), Visual Analogue Scale (VAS) for Fatigue and ECOG Performance Status (PS) were selected as clinical anchors. In the surgery group, MCID estimates for improvement and deterioration were ECOG PS (5*, 11*), GDS15 (5*, 2) and VAS Fatigue (3, 9*). In the chemotherapy group, MCID estimates for improvement and deterioration were ECOG PS (8*, 7*), GDS15 (5, 4) and VAS Fatigue (5, 5*). Estimates with * were > 0.2 SD threshold. Patients experiencing pain or malnutrition (surgery group) or fatigue (chemotherapy group) at baseline showed a significantly stable or improved HRQOL (p < 0.05) after their treatment. CONCLUSION: The reported MCID for improvement and deterioration depended on the anchor used and treatment received. The estimates can be used to evaluate significant changes in HRQOL and to determine sample sizes in clinical trials