A Distributed International Patient Data Registry for Hairy Cell Leukemia
Notice bibliographique
Résumé
Abstract BACKGROUND: The study of rare diseases is limited by the uncommon nature of the conditions as well as the widely dispersed patient populations. Current rare disease registries such as the National Organization of Rare Diseases utilize centralized platforms for data collection; however because of their broad nature, these do not always capture unique, disease specific elements. Hairy Cell Leukemia (HCL) is a rare leukemia globally with approximately 900 new cases diagnosed in the US each year. The HCL Foundation undertook creation of a Patient Data Registry that collects data from multiple HCL Centers of Excellence (COE) around the globe to better understand the complications, treatment outcomes, disease subtypes, comorbid conditions, epidemiology, and quality of life of patients with HCL. METHODS: Investigators at The Ohio State University Department of Biomedical Informatics and Division of Hematology in collaboration with the HCL Foundation developed a Patient Data Registry (PDR) for the longitudinal capture of high quality research data. This system differs from other registries in that it uses a federated( rather than centralized) architecture, wherein data is queried and integrated in an on-demand manner from local registry databases at each participating site. Further, the data collected for use in the registry combines both automated exports from existing electronic health records (EHRs) as well as additional data entered via a set of web-based forms. All manually entered data comes from source documents, and data provenance spanning electronic and manually entered data is maintained via multiple technical measures. Patients may be enrolled at HCL COE, or, if they do not have access to a COE they may enroll via a web-based portal (www.hairycellleukemia.org). At this time due to regulatory requirements the web-based portal is available to US patients only. All data are de-identified (see Figure 1: De-Identification Workflow) which reduces regulatory burden and increases opportunities for data access and re-use. End users have access to data via a project-specific query portal. RESULTS: The Patient Data Registry has been deployed at The Ohio State University, Royal Marsden Hospital, and MD Anderson Cancer Center, and is undergoing deployment at the University of Rochester. Up to 25 international HCL COE may participate. In addition, US patients are actively entering the registry via the web-based portal. To date, 227 patients have been consented to the registry with 119 of these being via the web-based entry point. CONCLUSION: We created an international and web-based patient data registry which will enable researchers to study outcomes in HCL in ways not previously possible given the rarity of the disease. This work was made possible by research funding from the Hairy Cell Leukemia Foundation. Figure De-Identification Workflow Figure. De-Identification Workflow Disclosures Andritsos: Hairy Cell Leukemia Foundation: Research Funding. Anghelina:Hairy Cell Leukemia Foundation: Research Funding. Lele:Hairy Cell Leukemia Foundation: Research Funding. Burger:Pharmacyclics: Research Funding. Delgado:Gilead: Consultancy, Honoraria; Novartis/GSK: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Research Funding; Infinity: Research Funding. Jones:AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics, LLC, an AbbVie Company: Membership on an entity's Board of Directors or advisory committees, Research Funding. Lozanski:Beckman Coulter: Research Funding; Genentech: Research Funding; Stemline Therapeutics Inc.: Research Funding; Boehringer Ingelheim: Research Funding. Montserrat:Morphosys: Other: Expert Testimony; Vivia Biotech: Equity Ownership; Gilead: Consultancy, Other: Expert Testimony; Pharmacyclics: Consultancy; Janssen: Honoraria, Other: travel, accommodations, expenses. Parikh:Pharmacyclics: Honoraria, Research Funding. Park:Genentech/Roche: Research Funding; Amgen: Consultancy; Juno Therapeutics: Consultancy, Research Funding. Robak:Pharmacyclics, LLC, an AbbVie Company: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding. Tam:janssen: Honoraria, Research Funding; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees. Heckler:Hairy Cell Leukemia Foundation: Research Funding. Payne:Hairy Cell Leukemia Foundation: Research Funding.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,021 | 0,033 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,007 | 0,011 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,015 | 0,007 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».