Key outcomes in treatment of activated phosphoinositide 3-kinase delta syndrome: An e-Delphi panel study and responder threshold application
Bibliographic record
Abstract
BACKGROUND: Activated phosphoinositide 3-kinase delta syndrome (APDS) is an ultra-rare, underrecognized inborn error of immunity. This study aimed to identify outcomes important in evaluating APDS treatment effectiveness and percent change in specific outcomes indicating a clinically meaningful benefit. METHODS: In this e-Delphi panel study, 28 globally based APDS experts used a 5-point Likert scale (Strongly Disagree to Strongly Agree) to indicate level of agreement that an outcome was an important measure of APDS treatment effectiveness in adult and pediatric patients at 3 and 6 months after treatment initiation. A threshold of ≥75% responding with "Agree" or "Strongly Agree" was considered consensus. Percent meaningful improvement in 6 outcomes was assessed and applied to APDS trial data (NCT02435173). RESULTS: Twenty-four panelists participated; e-Delphi rounds 1-5 were completed by 23, 21, 18, 17, and 16 panelists, respectively. Outcomes with the highest degree of consensus included lymph node size/volume, clinician overall impression of disease activity, antibiotic use, patient/caregiver-reported social outcomes and patient quality of life, hospitalizations, thrombocytopenia, spleen volume, lymphopenia, and anemia. Panelists indicated within-patient clinically meaningful improvements in adult patients ranged from median values of 20%-25% in lymph nodes, naïve B-cell to total B-cell ratio, spleen volume, hemoglobin, platelets, and lymphocytes at 3 months, and 25%-30% at 6 months. Panelists indicated within-patient clinically meaningful improvements in pediatric patients ranged from median values of 20%-27.5% at 3 months and 22.5%-45% at 6 months in the same 6 outcomes. In an application of responder thresholds, treatment with leniolisib resulted in significant and meaningful improvements in disease hallmarks, including lymph node size, spleen volume, and naïve B-cell ratio. CONCLUSION: This study provides expert consensus on outcomes important in assessing APDS treatment effectiveness and improvement thresholds in 6 treatment outcomes indicative of a clinically meaningful benefit. These outcomes may help optimize APDS treatment in the clinic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.170 | 0.132 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".