Patient-Reported Outcome Coordinator Did Not Improve Quality of Life Assessment Response Rates: A Report from the Children's Oncology Group
Bibliographic record
Abstract
PURPOSE: Health related quality of life (HRQL) assessments during therapy for pediatric cancer provide valuable information to better understand the patient experience. Our objective was to determine the impact of a patient-reported outcome (PRO) coordinator on HRQL questionnaire completion rates during a pediatric acute myeloid leukemia (AML) trial. METHODS: AAML1031 is a multicenter Children's Oncology Group therapeutic trial for de novo AML with a secondary aim to assess HRQL of children and adolescents treated with chemotherapy and hematopoietic stem cell transplantation (HSCT). Parents/guardians are the primary respondents and four questionnaires are administered at eight time points. The questionnaires are the PedsQL 4.0 Generic Core Scales, PedsQL 3.0 Acute Cancer Module, PedsQL Multidimensional Fatigue Scale, and the Pediatric Inventory for Parents. To improve response rates, a central PRO coordinator was instituted and reminded sites about upcoming and delinquent questionnaires. The proportion of HRQL questionnaires completed were compared prior to, and following institution of the PRO coordinator. This analysis evaluated the first five assessment time points. RESULTS: There were231 families who consented to participate in the HRQL aim. Overall response rates for all questionnaires were 73-83%. At time point 1, within 14 days of chemotherapy initiation, post-PRO coordinator completion rates were significantly higher for three of four questionnaires. However, the effect was not sustained and at time point 4, one month following last chemotherapy or HSCT, completion rates were significantly lower post-PRO coordinator for all four questionnaires. CONCLUSION: Addition of a central PRO coordinator did not result in sustained improvement in HRQL questionnaire completion rates. Efforts to improve response rates must consider other strategies.
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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 | 0.048 | 0.100 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".