Clinical Utility of Tumor Next-Generation Sequencing Panel Testing to Inform Treatment Decisions for Patients With Advanced Solid Tumors in a Tertiary Care Center
Bibliographic record
Abstract
PURPOSE There is limited information about the clinical utility of targeted next-generation sequencing (NGS) panel testing to inform decision making for patients with advanced solid tumors. The Ontario-wide Cancer Targeted Nucleic Acid Evaluation (OCTANE) is a prospective study that enrolled more than 4,500 patients with solid tumor for NGS panel testing. We performed a retrospective survey of medical oncologists to evaluate the impact of NGS testing on treatment decisions. METHODS Patients and treating oncologists were identified at the Princess Margaret Cancer Center between 2016 and 2021. Tumor-only sequencing was performed using a gene panel of either 555 or 161 cancer genes. Oncologists were asked to review testing results and complete a survey indicating whether NGS testing affected treatment decisions. The primary outcome of this study was rate of treatment change on the basis of mutation results. Patient, test, and physician factors were evaluated for association with treatment changes using univariate analyses and a mixed-effects model. RESULTS Of the 582 surveys sent, 394 (67.7%) were completed. We found that 188 (47.7%) patients had testing results classified as actionable by the oncologist and 62 (15.7%) patients were matched to treatment, of whom 37 (60%) were enrolled in a clinical trial, 13 (21%) received an approved drug, four (6%) were prescribed off-label therapy, and eight (13%) avoided ineffective treatment. Patient, test, and physician characteristics were not significantly associated with treatment change. There was no difference in overall survival between patients who received matched treatment versus those who did not ( P = .55, median survival not reached). CONCLUSION OCTANE testing led to a change in drug treatment in 15.7% of patients, supporting the clinical utility of NGS panel testing for patients with advanced solid tumors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".