دورية أكاديمية
Multivariable modeling of biomarker data from the phase 1 Foundation for the NIH Osteoarthritis Biomarkers Consortium
| العنوان: | Multivariable modeling of biomarker data from the phase 1 Foundation for the NIH Osteoarthritis Biomarkers Consortium |
|---|---|
| المؤلفون: | Hunter, David J, Deveza, Leticia A, Collins, Jamie E, Losina, Elena, Nevitt, Michael C, Roemer, Frank W, Guermazi, Ali, Bowes, Michael A, Dam, Erik B, Eckstein, Felix, Lynch, John A, Katz, Jeffrey N, Kwoh, C Kent, Hoffmann, Steve, Kraus, Virginia B |
| المصدر: | Hunter , D J , Deveza , L A , Collins , J E , Losina , E , Nevitt , M C , Roemer , F W , Guermazi , A , Bowes , M A , Dam , E B , Eckstein , F , Lynch , J A , Katz , J N , Kwoh , C K , Hoffmann , S & Kraus , V B 2022 , ' Multivariable modeling of biomarker data from the phase 1 Foundation for the NIH Osteoarthritis Biomarkers Consortium ' , Arthritis Care & Research , vol. 74 , .... |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | envir, psy |
| الوصف: | OBJECTIVE: To determine the optimal combination of imaging and biochemical biomarkers to predict knee osteoarthritis (OA) progression. METHODS: Nested case-control study from the FNIH OA Biomarkers Consortium of participants with Kellgren-Lawrence grade 1-3 and complete biomarker data (n=539 to 550). Cases were knees with radiographic and pain progression between 24-48 months from baseline. Radiographic progression only was assessed in secondary analyses. Biomarkers (baseline and 24-month changes) with p<0.10 in univariate analysis were selected, including MRI (quantitative (Q) cartilage thickness and volume; semi-quantitative (SQ) MRI markers; bone shape and area; Q meniscal volume), radiographic (trabecular bone texture (TBT)), and serum and/or urine biochemical markers. Multivariable logistic regression models were built using three different step-wise selection methods (complex vs. parsimonious models). RESULTS: Among baseline biomarkers, the number of locations affected by osteophytes (SQ), Q central medial femoral and central lateral femoral cartilage thickness, patellar bone shape, and SQ Hoffa-synovitis predicted progression in most models (C-statistics 0.641-0.671). 24-month changes in SQ MRI markers (effusion-synovitis, meniscal morphology, and cartilage damage), Q central medial femoral cartilage thickness, Q medial tibial cartilage volume, Q lateral patellofemoral bone area, horizontal TBT (intercept term), and urine NTX-I predicted progression in most models (C-statistics 0.680-0.724). A different combination of imaging and biochemical biomarkers (baseline and 24-month change) predicted radiographic progression only, with higher C-statistics (0.716-0.832). CONCLUSION: This study highlights the combination of biomarkers with potential prognostic utility in OA disease-modifying trials. Properly qualified, these biomarkers could be used to enrich future trials with participants likely to progress. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| العلاقة: | https://curis.ku.dk/portal/da/publications/multivariable-modeling-of-biomarker-data-from-the-phase-1-foundation-for-the-nih-osteoarthritis-biomarkers-consortiumTest(f355b1de-ba46-4a63-971c-1eb257fde3e6).html |
| الإتاحة: | https://doi.org/10.1002/acr.24557Test https://curis.ku.dk/portal/da/publications/multivariable-modeling-of-biomarker-data-from-the-phase-1-foundation-for-the-nih-osteoarthritis-biomarkers-consortiumTest(f355b1de-ba46-4a63-971c-1eb257fde3e6).html |
| حقوق: | undefined |
| رقم الانضمام: | edsbas.D6F52F06 |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |