Reasons for Lack of Referral to Medical Oncology for Systemic Therapy in Stage Iv Non-small-cell Lung Cancer: Comparison of 2003–2006 with 2010–2011
Bibliographic record
Abstract
Introduction: Only approximately 25% of stage iv non-small-cell lung cancer (nsclc) patients receive systemic therapy. For such patients, we examined factors affecting referral to a cancer centre (cc) and to medical oncology (mo), and use of systemic therapy. Methods: Using the Glans–Look Lung Cancer database, we completed a chart review of stage iv nsclc patients diagnosed in Southern Alberta during 2003–2006 and 2010–2011, comparing median overall survival (mos), referral, and treatment in the two cohorts. Results: Of the 922 patients diagnosed in 2003–2006 and the 560 diagnosed in 2010–2011, 94% and 82% respectively were referred to a cc, with 22% and 23% receiving traditional chemotherapy (tctx). Referral to a cc or mo and use of tctx correlated with survival (p < 0.0001): The mos duration was 11.2 months in those receiving tctx and 1.0 months in those not referred to a cc. The overall mos duration was similar in the two cohorts (4.1 months vs. 3.9 months, p = 0.47). Major reasons for lack of referral to mo included poor functional status, rapid decline, and patient wish, which were similar to the reasons for forgoing tctx. In the two cohorts, 87 (9.4%) and 42 (7.5%) patients received epidermal growth factor inhibitors, with a mos duration of 16.2 months. Multivariable analysis showed that male sex [hazard ratio (hr): 1.16; p = 0.008] and pulmonary embolus (hr: 1.2; p = 0.002) correlated with worse survival. In contrast, receipt of chemotherapy (hr: 0.5; p < 0.001) and enrolment in a clinical trial (hr: 0.76; p = 0.049) correlated with better survival. Conclusions: Our experience confirms that, over time, uptake of systemic therapy, including tctx and targeted therapy, changed little despite their established efficacy. Most of the factors limiting systemic therapy uptake appear to be non-modifiable at the time of referral. Rapid diagnosis and the availability of well-tolerated drugs for all nsclc patients will likely be the most important factors in increasing systemic therapy uptake in this population.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".