The clinical and economic burden of metastatic renal cell carcinoma in Canada in real-world setting
Bibliographic record
Abstract
Aim: The management of metastatic renal cell carcinoma (mRCC) has changed significantly in the past decade with the scientific advancement in the field of pharmacotherapy, the search for optimal timing of surgery and different ablation methods. In parallel, the economic burden of mRCC has grown with increased incidence and costly treatments. This research program aimed: 1) to evaluate effectiveness and costs of targeted therapy (sunitinib and pazopanib) in first-line setting in clear cell mRCC patients; 2) to develop a Markov model with Monte-Carlo simulations in order to assess the cost-utility of sunitinib vs. pazopanib in patients who have mRCC in first-line setting from the Canadian healthcare system perspective and 3) to evaluate the impact of metastasectomy on clinical outcomes in mRCC patients using real-world data from Canadian academic hospitals.For the first objective of this research program, the Canadian Kidney Cancer information system (CKCis), a pan-Canadian database, was used to identify prospectively collected mRCC patients’ data between January 2011 and December 2017. Survival curves (Kaplan-Meier, conditional survival and direct adjusted survival curves) were used to estimate the unadjusted and adjusted overall survival (OS) by treatment. Unit treatment cost was taken from the Régie d’assurance Maladie du Québec (RAMQ) list of medications to estimate the cost by line of treatment and the total cost of targeted therapy for the management of mRCC patients. We included 475 patients receiving sunitinib or pazopanib in the first-line setting. Patients were mostly treated with sunitinib (81%), and 19% of patients were treated with pazopanib. The adjusted OS with sunitinib was 32 months compared to 21 months with pazopanib (p=0.01). The total average first-line cost of treatment with sunitinib and pazopanib was $94,232 (95%CI: $74,059 - $114,169) and $70,000 (95%CI: $32,942 -$107,993), respectively.For the second objective, a Markov model with Monte-Carlo microsimulations was developed to estimate the clinical and economic outcomes of patients treated in first-line with sunitinib vs. pazopanib over a 5-year period. Transition probabilities were calculated using the effectiveness results from the first objective. The costs of therapies, disease progression, and management of adverse events were included in the model in Canadian dollars. The difference in quality-adjusted life year (QALY) was 0.54 in favour of sunitinib with an incremental cost-utility ratio (ICUR) of $67,227/QALY for sunitinib vs. pazopanib. The difference in life years gained (LYG) was 1.21 (33.51 vs. 19.03 months), and the incremental cost-effectiveness ratio (ICER) was $30,002/LYG. For the third objective, patients were stratified depending if they were managed with a complete or incomplete metastasectomy or no metastasectomy. A total of 417 patients had a complete (273 patients) and incomplete (144 patients) metastasectomy, respectively. At 12 months, 98.7%, 87.1% and 77.7% of patients were alive in the complete metastasectomy, incomplete metastasectomy and no metastasectomy group, respectively (p<0.001). After matching, patients who underwent complete metastasectomy had a longer overall survival (HR: 0.41, 95%CI:0.30-0.56) compared to patients who did not undergo metastasectomy, but this benefit was not shown in patients undergoing incomplete metastasectomy (HR: 0.95, 95%CI: 0.71-1.28) vs. non-metastasectomy patients.In conclusion, using the CKCis database, we have assessed the real-life utilization of resources such as pharmacotherapy and surgical management as well as their respective outcome on mRCC patients in Canada. Also, our cost-utility analysis is the first economic analysis based on real-world evidence, and positions well the clinical values found in our results with regards to the economic value of targeted 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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".