Pilot study of the effect of romiplostim on child health‐related quality of life (HRQoL) and parental burden in immune thrombocytopenia (ITP)
Bibliographic record
Abstract
BACKGROUND: Childhood ITP can have a negative impact on the child and his/her family even though it is typically a benign disorder with low risk of serious bleeding. In adults and now children, romiplostim increases the platelet count without significant adverse effects. In this study, the impact of romiplostim treatment on the HRQoL of children with chronic ITP was assessed using the Kid's ITP Tools (KIT). PROCEDURE: Subjects 1-18 years old, with chronic ITP (>6 months), were enrolled in a multi-center, randomized, double-blind, placebo-controlled phase 1/2 treatment study with romiplostim (reported elsewhere). Subjects and/or proxies completed the KIT at baseline, week 5, and week 13. Scores were computed for child self-report (children >7 years), proxy-report, and parent impact. Changes in mean scores from baseline to week 13 were computed. RESULTS: Twenty-two children (17 receiving romiplostim, 5 placebo) and/or their parents provided data. Change in mean scores demonstrated significant improvement in HRQoL for romiplostim versus placebo for parent impact (24 ± 17 vs. -6 ± 8; P = 0.008). Change scores for child self-report trended toward improvement with romiplostim and decreased with placebo (5 ± 10 vs. -7 ± 17; P = 0.29). Romiplostim proxy-report mean change scores were 6 points higher than placebo (8 ± 16 vs. 2 ± 12; P = 0.50). CONCLUSIONS: Romiplostim significantly reduced parental burden in this study. Whether the same and/or additional improvements in HRQoL would be demonstrated by a larger, longer study of romiplostim-treated children with ITP remains to be determined. Pediatr Blood Cancer 2012; 58: 395-398. © 2011 Wiley Periodicals, Inc.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".