Use of Targeted Therapy in Patients with Metastatic Renal Cell Carcinoma: Clinical and Economic Impact in a Canadian Real-Life Setting
Bibliographic record
Abstract
Introduction Outside of randomized controlled clinical trials, the understanding of the effectiveness and costs associated with targeted therapies for metastatic renal cell carcinoma (mrcc) is limited in Canada. The purpose of the present study was to use real-world prospective data to assess the effectiveness and cost of targeted therapies for patients with mrcc. Methods The Canadian Kidney Cancer Information System, a pan-Canadian database, was used to identify prospectively collected data relating to patients with mrcc. First- and subsequent-line time to treatment termination (ttt) was determined from therapy initiation time (sunitinib or pazopanib) to discontinuation of therapy. Kaplan– Meier survival curves were used to estimate the unadjusted and adjusted overall survival (os) by treatment. Unit treatment cost was used to estimate the cost by line of treatment and the total cost of therapy for the management of patients with mrcc. Results The study included 475 patients receiving sunitinib or pazopanib in the first-line setting. Patients were treated mostly with sunitinib (81%); 19% of patients were treated with pazopanib. The median ttt in the first line was 7.7 months for patients receiving sunitinib and 4.6 months for those receiving pazopanib (p < 0.001). The adjusted os was 32 months with sunitinib and 21 months with pazopanib (hazard ratio: 1.61; p < 0.01). The total median cost of first- and second-line treatments was $56,476 (interquartile range: $23,738–$130,447) for patients in the sunitinib group and $46,251 (interquartile range: $28,167–$91,394) for those in the pazopanib group. Conclusions For the two therapies, os differed significantly, with a higher median os being observed in the sunitinib group. The cost of treatment was higher in the sunitinib group, which is to be expected with longer survival.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".