Building a Healthcare Alliance for Resourceful Medicine Offensive Against Neoplasms in Hematology Added Value Framework for Hematologic Malignancies: A Comparative Analysis of Existing Tools
Bibliographic record
Abstract
OBJECTIVES: The Innovative Medicines Initiative-funded, multistakeholders project Healthcare Alliance for Resourceful Medicine Offensive Against Neoplasms in Hematology (HARMONY) created a task force involving patient organizations, medical associations, pharmaceutical companies, and health technology assessment/regulator agencies' representatives to evaluate the suitability of previously established value frameworks (VFs) for assessing the clinical and societal impact of new interventions for hematologic malignancies (HMs). METHODS: Since the HARMONY stakeholders identified the inclusion of patients' points of view on evaluating VFs as a priority, surveys were conducted with the patient organizations active in HMs and part of the HARMONY network, together with key opinion leaders, pharmaceutical companies, and regulators, to establish which outcomes were important for each HM. Next, to evaluate VFs against the sources of information taken into account (randomized clinical trials, registries, real-world data), structured questionnaires were created and filled by HARMONY health professionals to specify preferred data sources per malignancy. Finally, a framework evaluation module was built to analyze existing clinical VFs (American Society of Clinical Oncology, European Society of Medical Oncology, Magnitude of Clinical Benefit Scale, Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen, Institute for Clinical and Economic Review, National Comprehensive Cancer Network Evidence Blocks, and patient-perspective VF). RESULTS: The comparative analysis describes challenges and opportunities for the use of each framework in the context of HMs and drafts possible lines of action for creating or integrating a more specific, patient-focused clinical VF for HMs. CONCLUSIONS: None of the frameworks meets the HARMONY goals for a tool that applies to HMs and assesses in a transparent, reproducible, and systematic way the therapeutic value of innovative health technologies versus available alternatives, taking a patient-centered approach and using real-world evidence.
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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 | 0.241 | 0.236 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.023 | 0.018 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.002 | 0.004 |
| 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".