Less toxic chemotherapy on the uptake of all lines of chemotherapy in advanced non-small cell lung cancer: A 10-year retrospective population-based review.
Bibliographic record
Abstract
e19131 Background: The platinum doublet is standard first-line therapy in advanced NSCLC. Over the past decade, well-tolerated second-line therapies have been approved, including erlotinib and pemetrexed. We hypothesize that the introduction of less-toxic chemotherapy has increased treatment of advanced NSCLC, resulting in improved survival. Methods: The BC Cancer Agency provides cancer care to a population of 4.5 million. A retrospective review was conducted of all referred stage IIIB/IV patients in four 1-yr time cohorts; C1 baseline (1998) and 6 months after the provincial approval of C2 docetaxel (2001), C3 erlotinib (2006) and C4 pemetrexed (2007). Results: 2,623 patients were referred and 720 had systemic therapy. Characteristics: M/F 55%/45%, median age 67 (33-101), ECOG <=1/>=2/unknown 33%/56%/11%, never/former/current/unknown smoker 9%/35%/36%/20%, squam/nonsquam/NOS 18%/41%/41%. More patients received first-line chemotherapy over time; 16%, 23%, 34%, 33% C1-4 respectively. In C1 to C4 uptake of second line (21%, 27%, 38%, 55%) and third line (10%, 10% 14%, 18%) increased. In C1 the most common first-line doublet was cis/vino (70%) and in C4, cis/gem (45%). Second-line doce was frequently used in C2 (51%) but usage decreased in C4 to 7% vs. erlo 50% and pem 26%. In the >=70 group (n=1,118), first-line usage increased from C1 9% to C4 19% and second-line in the C2 (doce) 4% to C4 (erlo+pem avail) 56%. The increased use of systemic therapy was associated with improved survival in all patients: C1 4.56 m vs C4 4.98 m (p=0.004) and treated patients; C1 9.48 m vs C4 12.07 m (p=0.014) and the >= 70 group; C1 9.7 m vs C4 12.5 m (p=0.07). Conclusions: This population-based data set represents the trend of treatments over time in a large geographical area, including community and tertiary care cancer treatment sites. The introduction of less-toxic systemic therapy for advanced NSCLC resulted in an increased proportion of patients treated with first-line chemotherapy and an even greater increase in second-/third-line treatment. This trend was particularly evident in the elderly. Associated with this was a significant improvement in overall survival for all subsets.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".