Liver Iron Concentration By MRI In Chronically Transfused Children With Sickle Cell Anemia In The Twitch Trial
Notice bibliographique
Résumé
Abstract Introduction Chronic transfusion therapy represents the standard of care for sickle cell anemia (SCA) patients with abnormal transcranial Doppler (TCD) ultrasound or prior stroke. While effective, monthly transfusions produce iron overload and toxicity if not controlled with chelation therapies. Liver iron concentration (LIC) is a powerful surrogate for total body iron stores. Unfortunately, liver biopsy is not suited for longitudinal analysis because it is invasive, expensive, and prone to sampling variability. MRI transverse relaxation rates, R2 and R2*, are highly correlated with LIC and have mostly supplanted liver biopsy for iron quantification in clinical practice and clinical trials. Since R2 and R2* have different sensitivity to the size and scale of tissue iron distribution, we compared the agreement of LIC values predicted by R2 and R2* in children with SCA and transfusional iron overload from the prospective multicenter TCD with Transfusions Changing to Hydroxyurea (TWiTCH) trial (ClinicalTrials.gov; NCT01425307). Methods 133 patients underwent LIC assessment using both R2 and R2* techniques at 22 MRI sites. All sites used 1.5 Tesla magnets and torso phased array coils. Images for R2 measurements were collected on validated scanners and analyzed centrally according to the FerriScan” protocol (Resonance Health, Western Australia, see St Pierre, T.G., et al. Blood,105, 855-861, 2005). Images for R2* assessment were collected using multiple-echo gradient echo sequences (see Wood, J.C., et al. Blood,106, 1460-1465, 2005). Images were analyzed centrally at Children's Hospital Los Angeles, using an exponential-plus-constant fit to the signal decay. Bland-Altman analysis on log-transformed LIC values was used to test agreement between LICR2 and LICR2*; the residuals of this relationship were probed for association with transfusion/chelation history, markers of inflammation, and markers of hemolysis. Results Figure 1A illustrates the scattergram between LICR2* and LICR2. The variance of the disagreement between the two techniques increases with LIC, so log-transformation was performed prior to Bland Altman analysis. LICR2* was systematically higher than LICR2 below about 5 mg Fe/g dw and systematically lower above 5 mg Fe/g dw. Bland Altman comparison of the log-transformed data (Figure 1B) reveals a downward trend (r2 of 0.203, p<0.0001). After correcting for the trend, 95% limits of agreement were -0.42 to 0.42, translating to 95% limits of agreement of the ratio of the two LIC measurements of 0.66 to 1.52. After controlling for mean log LIC, differences in log LIC values were not associated with transfusion or chelation history, markers of inflammation, or markers of hemolysis. Discussion Systematic bias is present between LICR2 and LICR2* in a cohort of children with SCA and transfusional iron overload. Even after correcting these differences, LICR2 and LICR2* also demonstrate significant intrasubject variability, comparable to the error both techniques displayed with respect to biopsy, precluding use of these metrics interchangeably. This implies that LICR2 and LICR2* have potentially clinically significant deviations from true LIC. Rather than sampling or MRI measurement errors, which are consistently < 10% in multiple studies, these disparities likely reflect calibration bias introduced by intersubject differences in tissue iron distribution. Longitudinal LIC determination should lessen their impact, however, and the changes in LIC predicted by R2 and R2* will be compared using one and two year data from the TWiTCH trial. Disclosures: Wood: Novartis: Honoraria; Apopharma: Honoraria, Patents & Royalties; Shire: Consultancy, Research Funding. Off Label Use: Hydroxyurea is FDA-approved for use in adults but not children. Kwiatkowski:Shire: Consultancy; Resonance Health: Research Funding. St. Pierre:Resonance Health Ltd: Consultancy, Equity Ownership, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; Novartis: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding, Speakers Bureau.
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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 | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».