Barriers to personalized medicine in pediatrics: The implementation of a novel pharmacogenomic test for pediatric neuroblastoma
Bibliographic record
Abstract
Background: Primary brain tumours, specifically high-grade astrocytoma (HGA), are one of the leading causes of death from cancer in children under the age of 20. A novel laboratory derived pharmacogenomic (PGx) test has been developed and is well placed for use as a standard of care. The test is able diagnostically stratify the disease, it can readily identify whether or not a child is a carrier of a genetic mutation causing resistance to all available curative treatments. Knowledge of this mutation will move pediatric patients directly into palliative care; doing so will prevent the child from receiving harsh, ineffective treatments. Personalized medicine in pediatrics is often met with controversy; the practical and ethical barriers associated with this test must be explored prior to implementation. Objective: The purpose of the investigation was to evaluate relevant barriers associated with the use of the novel PGx test as a standard of care in clinical pediatric oncology. Methods: A mixed methods embedded design was used to explore the barriers perceived by the end users of the novel pharmacogenomic test; end users included healthcare professionals working in either pediatric palliative care or pediatric oncology. Deliberative stakeholder consultations were used to explore barriers associated with the test. Stakeholder deliberations are unique in that they promote a space for open discussion, with a goal of generating meaningful exchange and rich dialogue with informed stakeholders. The deliberations were followed by quantitative assessment using a tool aimed at evaluating the occurrence of deliberation and to measure the deliberation success. Consultations were recorded and a thematic analysis was conducted. Setting: The study took place at Montreal Children’s Hospital in Montreal, Quebec. Participants: End users of the test, including: pediatric oncologists, pediatric palliative care physicians, pediatric palliative care nurses, pediatric oncology nurses, bioethicists and a social worker, were recruited as stakeholders to participate in the deliberations. Results: A better understanding of the barriers surrounding the use of this novel PGx test was attained. Relevant barriers to implementation identified by stakeholders included: the role of palliative care in patient management, communication, the impact of the test on care and the existence of conflicting cultures of care between pediatric oncology and palliative care. Several minor themes were also identified, including: the need for training to prevent the patient’s experience of abandonment, difficulties with maintaining hope, providing inter-professional support and media as barrier. Results from the self-administered quantitative survey corroborated qualitative results showing that deliberation occurred; deliberative output was generated and it was concluded that a joint pre-clinic weekly meeting between pediatric oncology and pediatric palliative care would facilitate the introduction of this test as a standard of care. Conclusions: The study identified barriers that exist when implementing a pharmacogenomic test, capable of delivering a terminal diagnosis, as a standard of care in clinical pediatric oncology. It is hoped that this framework for exploring the implementation of a PGx test in clinical care can be generalized and used for other tests.
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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 | 0.052 | 0.109 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".