Chemotherapy Drug Shortages in Pediatric Oncology: A Consensus Statement
Bibliographic record
Abstract
Shortages of essential drugs, including critical chemotherapy drugs, have become commonplace. Drug shortages cost significant time and financial resources, lead to adverse patient outcomes, delay clinical trials, and pose significant ethical challenges. Pediatric oncology is particularly susceptible to drug shortages, presenting an opportunity to examine these ethical issues and provide recommendations for preventing and alleviating shortages. We convened the Working Group on Chemotherapy Drug Shortages in Pediatric Oncology (WG) and developed consensus on the core ethical values and practical actions necessary for a coordinated response to the problem of shortages by institutions, agencies, and other stakeholders. The interdisciplinary and multiinstitutional WG included practicing pediatric hematologist-oncologists, nurses, hospital pharmacists, bioethicists, experts in emergency management and public policy, legal scholars, patient/family advocates, and leaders of relevant professional societies and organizations. The WG endorsed 2 core ethical values: maximizing the potential benefits of effective drugs and ensuring equitable access. From these, we developed 6 recommendations: (1) supporting national polices to prevent shortages, (2) optimizing use of drug supplies, (3) giving equal priority to evidence-based uses of drugs whether they occur within or outside clinical trials, (4) developing an improved clearinghouse for sharing drug shortage information, (5) exploring the sharing of drug supplies among institutions, and (6) developing proactive stakeholder engagement strategies to facilitate prevention and management of shortages. Each recommendation includes an ethical rationale, action items, and barriers that must be overcome. Implemented together, they provide a blueprint for effective and ethical management of drug shortages in pediatric oncology and beyond.
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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 | 0.103 | 0.111 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.008 | 0.012 |
| Research integrity | 0.018 | 0.021 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".