Diffuse large B-cell lymphoma: A single-institution experience of patient outcomes.
Bibliographic record
Abstract
271 Background: The Windsor Regional Cancer Program (WRCP) was determined to have consistently been a top performer in time to treatment of diffuse large B cell lymphoma in this Canadian province (http://www.csqi.on.ca/by_type_of_cancer/lymphoma/lymphoma_treatment/). We endeavored to determine whether faster time to diagnosis and treatment for diffuse large B-cell lymphoma (DLBCL) influenced the IPI score (International Prognostic Score), thereby predicting an improved clinical outcome in these presenting patients. Methods: The WRCP services a catchment area of 650,000 people. A retrospective chart review was conducted for patients diagnosed with DLBCL at the Windsor Regional Cancer Program (WRCP) between 2006-2012. Information collected included the five factors for scoring by the International Prognostic Index (IPI) – age, performance status, LDH, stage, and number of extranodal sites – chemotherapy regimen, relapses, existence of second malignancies, cause of death, and dates of diagnosis, last follow-up, and death. We analyzed the relationship between prognostic factors and these clinical outcomes, and also compared the IPI scores for this cohort of patients against a similar population in another Canadian province, British Columbia. Results: It is established that compared to other cancer centres in Ontario, the WRCP is consistently reporting a shorter diagnosis to treatment metric when compared to their counterparts in Ontario, Canada. When compared to historical Canadian data, presenting IPI scores for DLBCL patients were lower on average for patients treated at the WRCP than those reported in British Columbia, Canada by Sehn et al. [Sehn, L. H., et al. (2007). The revised International Prognostic Index is a better predictor of outcome than the standard IPI for patients with diffuse large B-cell lymphoma treated with R-CHOP. Blood, 109(5), 1857-1861.]. Conclusions: A lower presenting IPI score is known to be correlated improved lymphoma related outcome. With attention to the metric of diagnosis to treatment < 30 days for diffuse large B cell lymphoma, we expect an improved lymphoma related outcome for our patients. We recommend ongoing attention to this metric, in order to improve outcomes for our patients.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".