Patterns in<i> KRAS</i> testing and EGFRi therapy across lines of treatment for metastatic colorectal cancer in Canada: A retrospective analysis.
Bibliographic record
Abstract
665 Background: Selection and sequencing of treatment regimens for individual metastatic colorectal cancer (mCRC) patients is governed by the goals of maintaining reasonable quality of life while extending survival. The timing of KRAS testing and its effect on EGFRi therapy is poorly described. The goals of this analysis wereto describe rates and timing of KRAS testing relative to EGFRi therapy for Canadian patients diagnosed with mCRC. Methods: A retrospective chart review conducted at 6 Canadian centres included patients diagnosed with mCRC from Jan 1, 2009 onwards, who commenced 1st-line systemic treatment for mCRC between Jan 1–Dec 31, 2009. Information on the proportion of patients who received 2nd, 3rd, or subsequent lines of systemic therapy for mCRC was determined and the rates and timing of KRAS testing was ascertained. Results: 200 patients commenced 1st-line therapy and the median age was 62 yr; 78% had mCRC at the time of diagnosis. The proportions of patients who started 2nd, 3rd, and 4th lines of systemic therapy were 70%, 30%, and 15%, respectively. 103 (52%) patients had KRAS testing; 6%, 18%, 57%, 16%, 2%, and 1% of patients were tested at diagnosis or before the 2nd, 3rd, 4th, 5th and 6th lines of therapy, respectively. Median time from testing to EGFRi treatment was 105 (range, 7–1192) days, and varied by site. The frequency of KRAS testing for patients ranged from 30%–70% across study sites; across provinces, the frequency of testing ranged from 46%–60%. 38/68 (56%) of patients with wt KRAS tumors received EGFRi; 31 (46%) patients received EGFRi therapy as next therapy following KRAS testing. 19 (28%) died and 4 were lost to follow-up within 120 days of KRAS testing with no other therapy. 2 additional patients with unknown KRAS status received EGFRi (1 without KRAS testing; 1 undetermined). Conclusions: KRAS testing occurred after starting 2nd line in 76% of cases and varied by site and province. About half of patients underwent KRAS testing and 56% of those patients with wt KRAS tumors received an EGFRi. The short time interval between (K)RAS testing and EGFRi therapy may point to the need for earlier testing if EGFRi therapy is to be used in earlier lines of therapy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".