Patient‐reported outcomes provide prognostic information for survival in patients with diffuse large B‐cell lymphoma: Analysis of 1239 patients from the <scp>GOYA</scp> study
Bibliographic record
Abstract
PURPOSE: We investigated the prognostic value of pretreatment patient-reported outcomes (PROs) in patients with diffuse large B-cell lymphoma (DLBCL) receiving obinutuzumab/rituximab plus chemotherapy in the GOYA phase III study. METHODS: Patients completed the European Organization for Research and Treatment of Cancer Quality of Life (EORTC QLQ-C30) and the Functional assessment of chronic illness therapy-Lymphoma (FACT-Lym) lymphoma subscale (LYMS) during the study. PRO scales with high prognostic value were identified through Cox regression analyses of overall survival (OS) and progression-free survival (PFS). These scales were evaluated in terms of their additional prognostic value beyond the International Prognostic Index (IPI). A preliminary assessment was performed to evaluate whether the scales provided improved patient-risk stratification beyond IPI. RESULTS: One thousand two hundred and fifty-nine patients with valid pretreatment PRO scales were included in the analyses, and complete pretreatment data were available for 1239/1414 patients (87.6%). Four PRO scales with high prognostic value were identified: FACT-Lym LYMS and EORTC QLQ-C30 physical functioning, global health status/quality of life (QoL), and fatigue. All four scales retained significant prognostic value for OS and PFS after IPI adjustment (all p < 0.05). After adjusting for multiple clinical variables (IPI, cell of origin, BCL2 status, and total metabolic tumor volume), all four scales retained significant prognostic value (all p < 0.05) for OS. Only the EORTC QLQ-C30 physical functioning scale was significant (p < 0.05) for PFS after adjustment for multiple clinical variables. CONCLUSIONS: In this large population of patients with DLBCL, pretreatment PROs provided prognostic information for OS and PFS beyond the well-established IPI.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".