SSPedi and SPARK: Promise for the future of electronic patient reported outcomes in pediatric oncology
Bibliographic record
Abstract
Objective Progress toward incorporating patient-reported outcomes (PROs) into the routine clinical care of pediatric cancer patients has accelerated over the last decade. Objective was to review general PRO considerations for pediatric cancer patients, describe the impact of PROs from adult cancer trials, summarize Symptom Screening in Pediatrics Tool (SSPedi) suite development and validation, and highlight recent clinical trials evaluating SSPedi implementation. Methods This review addressed the following topics: instrument choice, respondent type, lessons learned from adult oncology trials, SSPedi tools, recent randomized controlled trials (RCTs) of symptoms screening using SSPedi, and future directions. Results Instrument choice should be guided by the purpose of the assessment, where reasons include monitoring for adverse effects during cancer treatment clinical trials, choice as primary or secondary outcomes for supportive care clinical trials, and enabling routine symptom screening to enhance clinical care. While pediatric patient self-report of subjective symptoms is ideal, it may not always be feasible and careful consideration of respondent type is required. Instruments developed for use by different respondent types will likely be required for clinical implementation. Both adult and pediatric trials have demonstrated the value of symptom screening and support its adoption into routine clinical care. Two recent RCTs have shown that administration of SSPedi can improve symptom control in pediatric cancer patients. Conclusions There have been many advancements in PROs for pediatric cancer patients. Identifying approaches to feasibly implement symptom screening into routine clinical care is required. In the future, routine monitoring of symptoms should be a measure of quality of care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".