Influence of Treating Facility, Provider Volume, and Patient-Sharing on Survival of Patients With Multiple Myeloma
Bibliographic record
Abstract
BACKGROUND: Population-based studies suggest that patients with multiple myeloma (MM) have better outcomes when treated at high-volume facilities, but the relative contribution of provider expertise and hospital resources to improved outcomes is unknown. This study explored how treating facility, individual provider volume, and patient-sharing between MM specialists and community providers influenced outcomes for patients with MM. PATIENTS AND METHODS: A state cancer registry linked to public and private insurance claims was used to identify a cohort of patients diagnosed with MM in 2006 through 2012. Three multivariable Cox models were used to examine how the following factors impacted overall survival: (1) evaluation at an NCI-designated Comprehensive Cancer Center (NCICCC), (2) the primary oncologist's volume of patients with MM, and (3) patient-sharing between MM specialists and community oncologists. RESULTS: A total of 1,029 patients diagnosed with MM in 2006 through 2012 were identified. Patients who were not evaluated at an NCICCC had an increased risk of mortality compared with those evaluated at an NCICCC (hazard ratio [HR], 1.50; 95% CI, 1.21-1.86; P<.001). Compared with patients treated by NCICCC MM specialists, those treated by both low-volume community providers (HR, 1.47; 95% CI, 1.14-1.90; P<.01) and high-volume community providers (HR, 1.29; 95% CI, 1.04-1.61; P<.05) had a higher risk of mortality. No difference in mortality was seen between patients treated by NCICCC MM specialists and those treated by the highest-volume community oncologists in the ninth and tenth deciles (HR, 1.08; 95% CI, 0.84-1.37; P=.5591). Patients treated by community oncologists had a higher risk of mortality regardless of patient-sharing compared with patients treated by MM specialists (eg, community oncologist with a history of sharing vs NCICCC MM specialist: HR, 1.49; 95% CI, 1.10-2.02; P<.05). CONCLUSIONS: Findings of this study add to the accumulating evidence showing that patients with MM benefit from care at high-volume facilities, and suggest that similar outcomes can be achieved by the highest-volume providers in the community.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".