Date Of Progression Research Articles

Intra-read analysis of radiologists in the setting of blinded independent central review of oncology studies.

11179 Background: This study explored the outcome of an analysis completed on the Intra-reader variability of radiologists when assessing the imaging endpoint surrogates of Date of Progression (DOP) and Best Overall Response (BOR) within the context of Blinded Independent Central Review (BICR) in Oncology clinical trials. The analysis encompassed 55,000 test cases derived from 217 clinical trials involving 138 readers. Methods: Data collection and parsing were executed through a Python script, enabling a manual analysis of the results. The analysis posited that Intra-read variability serves as a valuable tool when seeking to exclusively observe the consistency of readers in a specific re-read setting. Results: The data analysis yielded significant insights, revealing that 89.81% of readers demonstrated substantial and above agreement in DOP determinations, while 72.38% achieved the same in BOR determinations. This suggests a higher level of consistency in DOP compared to BOR determination. Notably, 11 DOP and 20 BOR inconsistencies were observed. This prompted further investigation which led to 5 of the 138 readers being flagged based on discrepancies against their own prior or subsequent reads. The kappa values for these 5 readers ranged from 0.33 to 0.59, consistently indicating fair and moderate agreement. Conclusions: This analysis underscored the role of Intra-read variability in identifying inconsistent readers within the landscape of BICR in Oncology clinical trials. The re-read inconsistency is not a universal requirement, and its application is recommended primarily for complex oncology clinical trials or those with indications known to have elevated adjudication metrics. The study emphasized the potential for targeted retraining strategies based on Intra-read analysis outcomes, contributing to the ongoing refinement of reader proficiency. Future directions may involve further exploration of specific retraining strategies or assessing the effectiveness of exclusively using Intra-read variability as a metric for reader performance.

Impact of disease progression date determination on progression‐free survival estimates in advanced lung cancer

In patients with advanced lung cancer, overall survival is largely influenced by progression status. Because progression-free survival (PFS)-based endpoints are controversial, the authors evaluated the impact of the progression date (PD) determination approach on PFS estimates. Individual patient data from 21 trials (14 North Central Cancer Treatment Group trials and 7 Southwest Oncology Group trials) were used. The reported PD (RPD) was defined as either the radiographic scan date or the clinical deterioration date. PD was determined using Method 1 (M1), the RPD; M2, 1 day after the last progression-free scan; M3, midpoint between the last progression-free scan and the RPD; and M4, an interval-censoring approach. PFS was estimated using Kaplan-Meier (M1-M3), and maximum-likelihood (M4) methods. Simulation studies were performed to understand the impact of the length of time elapsed between the last progression-free scan and the PD on time-to-progression estimates. PFS estimates using the RPD were the highest, and M2 was the most conservative. M3 and M4 were similar because the majority of progressions occurred during treatment (ie, frequent disease assessments). M3 was influenced less by the length of the assessment schedules (percentage difference from the true time-to-progression, <1.5%) compared with M1 (11% to 30%) and M2 (-8% to -29%). The overall study conclusion was unaffected by the method used for randomized trials. The magnitude of difference in the PFS estimates was large enough to alter trial conclusions in patients with advanced lung cancer. The results indicate that standards for PD determination, the use of sensitivity analyses, and randomized trials are critical when designing trials and reporting efficacy using PFS-based endpoints.