Flexible multistate models for interval-censored data: Specification, estimation, and an application to ageing research.

Continuous-time multistate survival models can be used to describe health-related processes over time. In the presence of interval-censored times for transitions between the living states, the likelihood is constructed using transition probabilities. Models can be specified using parametric or semiparametric shapes for the hazards. Semiparametric hazards can be fitted using P-splines and penalised maximum likelihood estimation. This paper presents a method to estimate flexible multistate models that allow for parametric and semiparametric hazard specifications. The estimation is based on a scoring algorithm. The method is illustrated with data from the English Longitudinal Study of Ageing.

Transitions across cognitive states and death among older adults in relation to education: A multistate survival model using data from six longitudinal studies.

INTRODUCTION: This study examines the role of educational attainment, an indicator of cognitive reserve, on transitions in later life between cognitive states (normal Mini-Mental State Examination (MMSE), mild MMSE impairment, and severe MMSE impairment) and death. METHODS: Analysis of six international longitudinal studies was performed using a coordinated approach. Multistate survival models were used to estimate the transition patterns via different cognitive states. Life expectancies were estimated. RESULTS: Across most studies, a higher level of education was associated with a lower risk of transitioning from normal MMSE to mild MMSE impairment but was not associated with other transitions. Those with higher levels of education and socioeconomic status had longer nonimpaired life expectancies. DISCUSSION: This study highlights the importance of education in later life and that early life experiences can delay later compromised cognitive health. This study also demonstrates the feasibility and benefit in conducting coordinated analysis across multiple studies to validate findings.

Real-World Progression-Free Survival as an Endpoint in Lung Cancer: Replicating Atezolizumab and Docetaxel Arms of the OAK Trial Using Real-World Data.

Evaluating cancer treatments in real-world data (RWD) requires informative endpoints. This study replicated the atezolizumab and docetaxel arms of the OAK trial using RWD and compared progression-free survival (PFS) outcomes derived from abstracted physician's notes in RWD (rwPFS) against PFS outcomes derived from the clinical trial PFS (ctPFS). Atezolizumab and docetaxel arms of the phase III OAK randomized controlled trial (RCT; NCT02008227) were replicated in a US nationwide real-world database using selected OAK inclusion/exclusion criteria and propensity score-based adjustment for baseline prognostic variables. Concordance of outcomes was assessed using Kaplan-Meier medians and hazard ratios (HRs). The RWD cohorts comprised 133 patients on atezolizumab and 479 patients on docetaxel. After adjustment, prognostic variables were balanced between RCT arms and corresponding RWD cohorts. The rwPFS and ctPFS outcomes showed better concordance for docetaxel (2.99 vs. 3.52 months; HR: 0.99, 95% confidence interval (CI): 0.85-1.15) than for atezolizumab (3.71 vs. 2.76 months; HR: 0.8, 95% CI: 0.61-1.02). Excluding events labeled "pseudo-progression" from both RWD and RCT improved concordance for atezolizumab (4.24 vs. 4.14 months; HR: 0.95, 95% CI: 0.70-1.25). These findings were robust across sensitivity analyses. Replicating RCTs using RWD and comparing outcomes can help characterize RWD endpoints. Similarity of results between rwPFS and ctPFS at the cohort level may depend on drug category, highlighting the need for further studies to verify and understand when the corresponding outcomes can be compared, including within the same patient.

Replication of Overall Survival, Progression-Free Survival, and Overall Response in Chemotherapy Arms of Non-Small Cell Lung Cancer Trials Using Real-World Data.

PURPOSE: The utility of real-world data (RWD) for use as external controls in drug development is informed by studies that replicate trial control arms for different endpoints. The purpose of this study was to replicate control arms from four non-small cell lung cancer (NSCLC) randomized controlled trials (RCT) to analyze overall survival (OS), progression-free survival (PFS), and overall response rate (ORR) using RWD. PATIENTS AND METHODS: This study used RWD from a nationwide de-identified database and a clinico-genomic database to replicate OS, PFS, and ORR endpoints in the chemotherapy control arms of four first-line NSCLC RCTs evaluating atezolizumab [IMpower150-wild-type (WT), IMpower130-WT, IMpower131, and IMpower132]. Additional objectives were to develop a definition of real-world PFS (rwPFS) and to evaluate the real-world response rate (rwRR) endpoint. RESULTS: Baseline demographic and clinical characteristics were balanced after application of propensity score weighting methods. For rwPFS and OS, RWD external controls were generally similar to their RCT control counterparts. Across all four trials, the hazard ratio (HR) point estimates comparing trial controls with external controls were closer to 1.0 for the PFS endpoint than for the OS endpoint. An exploratory assessment of rwRR in RWD revealed a slight but nonsignificant overestimation of RCT ORR, which was unconfounded by baseline characteristics. CONCLUSIONS: RWD can be used to reasonably replicate the OS and PFS of chemotherapy control arms of first-line NSCLC RCTs. Additional studies can provide greater insight into the utility of RWD in drug development.

Real-world data prognostic model of overall survival in patients with advanced NSCLC receiving anti-PD-1/PD-L1 immune checkpoint inhibitors as second-line monotherapy.

BACKGROUND AND AIM: The objective of this retrospective, observational, noninterventional cohort study was to investigate prognostic factors of overall survival (OS) in patients with advanced non-small cell lung cancer (aNSCLC) and to develop a novel prognostic model. METHODS: A total of 4049 patients with aNSCLC diagnosed between January 2011 and February 2020 who received atezolizumab, nivolumab, or pembrolizumab as second-line monotherapy were selected from a real-world deidentified database to build the cohort. Patients could not have received first-line treatment with clinical study drug(s) nor immune checkpoint inhibitors including anti-programmed cell death 1 (PD-1)/programmed death-ligand 1 (PD-L1), and anti-cytotoxic T-lymphocyte-associated protein 4 therapies. RESULTS: Patients had a median age of 69 years; 45% were female, 75% White, 70% had stage IV at initial diagnosis, and 70% had nonsquamous histology. A Cox proportional hazards model with lasso regularization was used to build a prognostic model for OS using 18 baseline demographic and clinical factors based on the real-world data cohort. The risk-increasing prognostic factors were abnormally low albumin and chloride levels, Eastern Cooperative Oncology Group performance status score ≥ 2, and abnormally high levels of alkaline phosphatase and white blood cells. The risk-decreasing prognostic factors were PD-L1 positivity, longer time from advanced diagnosis to start of first-line therapy, and higher systolic blood pressure. The performance of the model was validated using data from the OAK trial, and the c-index for the OAK trial validation cohort was 0.65 and 0.67 for the real-world data cohort. CONCLUSIONS: Based on baseline demographic and clinical factors from a real-world setting, this prognostic model was developed to discriminate the risk of death in patients with aNSCLC treated with checkpoint inhibitors as second-line monotherapy, and it performed well in the real-world data and clinical trial cohorts.