Learnings From Precision Clinical Trial Matching for Oncology Patients Who Received NGS Testing

Abstract

PURPOSE Tumor next-generation sequencing reports typically generate trial recommendations for patients based on their diagnosis and genomic profile. However, these require additional refinement and prescreening, which can add to physician burden. We wanted to use human prescreening efforts to efficiently refine these trial options and also elucidate the high-value parameters that have a major impact on efficient trial matching. METHODS Clinical trial recommendations were generated based on diagnosis and biomarker criteria using an informatics platform and were further refined by manual prescreening. The refined results were then compared with the initial trial recommendations and the reasons for false-positive matches were evaluated. RESULTS Manual prescreening significantly reduced the number of false positives from the informatics generated trial recommendations, as expected. We found that trial-specific criteria, especially recruiting status for individual trial arms, were a high value parameter and led to the largest number of automated false-positive matches. CONCLUSION Reflex clinical trial matching approaches that refine trial recommendations based on the clinical details as well as trial-specific criteria have the potential to help alleviate physician burden for selecting the most appropriate trial for their patient. Investing in publicly available resources that capture the recruiting status of a trial at the cohort or arm level would, therefore, allow us to make meaningful contributions to increase the clinical trial enrollments by eliminating false positives.

Brief Report: Implementation of a Universal Prescreening Protocol to Increase Recruitment to Lung Cancer Studies at a Veterans Affairs Cancer Center

“… 14 Nevertheless, many such systems are not yet mature, have high false-positive rates, and demonstrate the current necessity of manual review for a reliable process. 15 Our work reveals that a mostly manual prescreening protocol increases enrollment to lung cancer clinical trials, and we believe that our methods can provide guidance, input, and validation as decision support tools mature.…”

Computational methods and translational applications for targeted next‐generation sequencing platforms

“…68 To facilitate this task and provide support to treating physicians, knowledge bases such as OncoKB 28 and CIVIC, 29 among others, 3 have been developed in recent years and are kept regularly updated to reflect the latest advancements in the field. Multiple institutions are also currently using results from NGS testing to match patients with ongoing clinical trials based on their genomic profiles 69,70 and computational pipelines like MatchMiner 39 have been specifically designed for this purpose. Liquid biopsy tests built upon panel-based NGS assays to detect and quantify tumorderived cell-free DNA (cfDNA) can also be used for longitudinal monitoring of response to treatment, as well as early detection of tumor relapse and monitoring of minimal residual disease after certain treatments.…”

“…The effort aims to standardize and structure real-world clinical data according to the PRISSMM model proposed by DFCI. 69 The effort will first focus on bladder, breast, colorectal, lung, pancreatic, and prostate cancer patients, with the goal of expanding to other cancer types and other institutions at a later phase. As of November 2021, the first analyses of integrated clinical and genomic data for the lung and colorectal cohort have already been published, [75][76][77] highlighting the great potential for translational research of a resource of this type.…”

“…To address this gap in the data, GENIE has launched a collaboration with nine biopharmaceutical companies with the goal of obtaining detailed clinical data for an estimated subset of 50 000 patients within an initial period of 5 years. The effort aims to standardize and structure real‐world clinical data according to the PRISSMM model proposed by DFCI 69 . The effort will first focus on bladder, breast, colorectal, lung, pancreatic, and prostate cancer patients, with the goal of expanding to other cancer types and other institutions at a later phase.…”

My Cancer Genome: Coevolution of Precision Oncology and a Molecular Oncology Knowledgebase

“…Current guidelines recommend patients be managed on clinical trials, 3 many of which include molecularly targeted interventions and biomarker-based inclusion criteria. [4][5][6] Recognizing the rapid expansion of precision oncology, in collaboration with clinicians and experts, we developed My Cancer Genome (MCG), 7 the first resource to provide publicly available, detailed information on cancer-related genetic variants geared toward clinicians. [8][9][10][11] MCG has distinguished itself through its inclusion of clinical trials and organization of content along cancer-relevant cell-signaling pathways.…”