MétaCan
Menu
Back to cohort

PF328 PREDICTORS OF TREATMENT RESPONSE TO IMMUNOSUPPRESSANTS IN ACQUIRED HEMOPHILIA A

2019· article· en· W2950544845 on OpenAlexaff
Wai-lee Lau, Mo-ching Leung, Psf Yip, K.M. C. Cheung, Susanne Lau, K.K. H. Lee, Wing-Sze Mak, Stanley Ho, C.H. K. Kwok

Bibliographic record

VenueHemaSphere · 2019
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineInternal medicineAdverse effectProportional hazards modelPartial thromboplastin timePopulationSingle CenterRetrospective cohort studyCoagulation

Abstract

fetched live from OpenAlex

Background: Acquired hemophilia A (AHA) is a rare bleeding disorder, caused by inhibitors against factor VIII, which may result in life‐threatening bleeding. Management of AHA is two pronged ‐ to arrest bleeding with hemostatic agent and to eradicate FVIII inhibitors by immunosuppressants. However, immunosuppressants are associated with frequent adverse events, with infection being the leading cause of morbidity and mortality. Identifying predictors of treatment response may help tailor treatment strategies and reduce treatment associated adverse events. Aims: The aims of the study were to evaluate the presenting features, treatment, and outcomes of patients with AHA in our local population, to identify the predictors of normalization of aPTT after immunosuppressive therapy and overall survival; and to investigate the patient characteristics that predict normalization of aPTT by steroid alone within 6 weeks. Methods: This was a retrospective multi‐center study which recruited 108 patients diagnosed with AHA between 1st January 2002 and 31st December 2016. AHA is defined by the presence of a neutralizing FVIII inhibitor ≥ 0.6 Bethesda units (BU)/ml and a FVIII activity <50%. Patients with congenital hemophilia A with inhibitors were excluded. Prognostic factors for normalization of aPTT and overall survival were analyzed using Cox proportional hazards regression analysis. Results: Normalization of aPTT was an independent predictor of overall survival (OR 0.14, 95% CI 0.07–0.27, P < 0.001). Patients with ECOG performance status ≤2 were more likely to attain normal aPTT (HR 2.09, 95% CI 1.28–3.42, P 0.003) while patients with underlying autoimmune diseases were less likely to achieve normal aPTT (HR 0.46, 95% CI 0.23–0.91, P 0.027). Female (OR 3.73, CI 1.15–12.2, P 0.028) and an inhibitor titer ≤20 BU/ml (OR 4.3, CI 1.36–13.63, P 0.013) predicted a higher chance of normalization of aPTT with steroid alone within 6 weeks. Summary/Conclusion: Identification of patients who are more likely to respond to steroid alone within 6 weeks may avoid unnecessary immunosuppressants and thus reduce treatment‐related adverse events. This finding may help individualize treatment strategies. Normalization of aPTT was an independent prognostic factor of survival. This finding echoed other studies and reiterated the importance of achieving remission. To date, the optimal immunosuppressive strategy remains elusive. Further high‐quality evidence is needed to guide the choice and intensity of treatment.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.021
GPT teacher head0.303
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueHemaSphereSame topicHemophilia Treatment and ResearchFrench-language works237,207