Biomarker inference and the timing of next-generation sequencing in a multi-institutional, cross-cancer clinicogenomic data set Journal Article
| Authors: | Kehl, K. L.; Lavery, J. A.; Brown, S.; Fuchs, H.; Riely, G.; Schrag, D.; Newcomb, A.; Nichols, C.; Micheel, C. M.; Bedard, P. L.; Sweeney, S. M.; Fiandalo, M.; Panageas, K. S.; on behalf of the AACR Project GENIE BPC Core Team |
| Article Title: | Biomarker inference and the timing of next-generation sequencing in a multi-institutional, cross-cancer clinicogenomic data set |
| Abstract: | PURPOSEObservational clinicogenomic data sets, consisting of tumor next-generation sequencing (NGS) data linked to clinical records, are commonly used for cancer research. However, in real-world practice, oncologists frequently request NGS in search of treatment options for progressive cancer. The extent and impact of this dynamic on analysis of clinicogenomic research data are not well understood.METHODSWe analyzed clinicogenomic data for patients with non-small cell lung, colorectal, breast, prostate, pancreatic, or urothelial cancers in the American Association for Cancer Research Biopharmaceutical Consortium cohort. Associations between baseline and time-varying clinical characteristics and time from diagnosis to NGS were measured. To explore the impact of informative cohort entry on biomarker inference, statistical interactions between selected biomarkers and time to NGS with respect to overall survival were calculated.RESULTSAmong 7,182 patients, time from diagnosis to NGS varied significantly by clinical factors, including cancer type, calendar year of sequencing, institution, and age and stage at diagnosis. NGS rates also varied significantly by dynamic clinical status variables; in an adjusted model, compared with patients with stable disease at any given time after diagnosis, patients with progressive disease by imaging or oncologist assessment had higher NGS rates (hazard ratio for NGS, 1.61 [95% CI, 1.45 to 1.78] and 2.32 [95% CI, 2.01 to 2.67], respectively). Statistical interactions between selected biomarkers and time to NGS with respect to survival, potentially indicating biased biomarker inference results, were explored.CONCLUSIONTo evaluate the appropriateness of a data set for a particular research question, it is crucial to measure associations between dynamic cancer status and the timing of NGS, as well as to evaluate interactions involving biomarkers of interest and NGS timing with respect to survival outcomes. © 2024 by American Society of Clinical Oncology. |
| Keywords: | adult; aged; gene mutation; major clinical study; overall survival; pancreas cancer; cancer staging; colorectal cancer; breast cancer; epidermal growth factor receptor; cohort analysis; protein p53; cancer research; prostate cancer; medical society; genomics; k ras protein; transitional cell carcinoma; b raf kinase; non small cell lung cancer; cancer prognosis; high throughput sequencing; human; male; female; article; mortality risk |
| Journal Title: | JCO Precision Oncology |
| Volume: | 8 |
| ISSN: | 2473-4284 |
| Publisher: | American Society of Clinical Oncology |
| Date Published: | 2024-09-01 |
| Start Page: | e2300489 |
| Language: | English |
| DOI: | 10.1200/po.23.00489 |
| PUBMED: | 38484212 |
| PROVIDER: | scopus |
| PMCID: | PMC10954072 |
| DOI/URL: | |
| Notes: | Article -- MSK Cancer Center Support Grant (P30 CA008748) acknowledged in PubMed and PDF -- Source: Scopus |
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