The study analyzed 20 clinical prediction models (CPMs) for rheumatoid arthritis (RA), all of which were deemed to have a high risk of bias, leading the researchers to urge against their use to guide decision-making without addressing their limitations.
There is a need for clinical prediction models (CPMs) that can successfully guide providers in using methotrexate for the treatment of rheumatoid arthritis, found a systemic review and meta-analysis.
The study analyzed 20 CPMs from 13 studies and 4 validation studies, all of which were deemed as having a high risk of bias (ROB), leading the researchers to urge against their use to guide decision making without addressing their limitations. The group largely attributed this to small sample sizes, lack of validation, insufficient handling of missing data, inconsistent reporting, and failure to account for discontinuation rates due to adverse events (AEs).
Their findings were published in Seminars in Arthritis & Rheumatism.
“Only one study predicted discontinuation due to AEs and model performance was poor. This may be due to the small outcome prevalence compared to predicting treatment response as defined through the DAS28 [health assessment questionnaire],” explained the researchers. “A relatively small outcome prevalence may result in low statistical power, leading to risk models making inaccurate predictions. As various outcome definitions are currently used, further input from patients and prescribers on which outcomes are clinically important may be valuable.”
In addition to AEs, outcomes analyzed in the study included state of disease activity and European Alliance of Associations for Rheumatology response criteria. According to the researchers, most models were able to predict state of disease activity, which they note may be due to treat-to-target recommendations that promote remission or low disease activity as quickly and safely as possible.
Just one model accounted for potential competing risks, an approach that could offer more realistic and clinically relevant predictions, the group wrote. Forty-rive percent of models were internally validated using recommended resampling techniques in the development dataset to correct for optimism.
Across the CPMs, the researchers found a lack of data reporting on certain patient characteristics, including comorbidities, which play an important role in methotrexate prescribing and response. Forty-rive percent of models included data on concomitant antirheumatic treatment.
There were 8 (40%) models that used multiple imputation to account for missing data, producing various plausible datasets and averaging results across each, which the researchers noted is considered a robust approach to account for missing data. The other models used complete case analysis, which is limited to patients with full baseline data available, resulting in smaller sample size for analysis.
“There are, however, some encouraging results identified by our review, as ROB was universally rated as low in the participants, predictors, and outcome domains, and the meta-analysis showed overall good performance of the 2 CPMs with multiple external validations,” described the researchers. “Therefore, once the methodological limitations outlined above are addressed, there is scope to develop an accurate CPM of methotrexate outcomes to guide treatment decisions in rheumatoid arthritis (upon undertaking appropriate impact assessment studies). However, even if patients at high risk of poor response of methotrexate were successfully identified, there is currently no clear indication that they will respond better to alternative therapies, such as biological disease-modifying antirheumatic drugs.”
Reference
Gehringer C, Martin G, Hyrich K, Verstappen S, Sergeant J. Clinical prediction models for methotrexate treatment outcomes in patients with rheumatoid arthritis: a systematic review and meta-analysis. Semin Arthritis Rheum. Published online July 31, 2022. doi:10.1016/j.semarthrit.2022.152076
Oncology Onward: A Conversation With Thyme Care CEO and Cofounder Robin Shah
October 2nd 2023Robin Shah, CEO of Thyme Care, which he founded in 2020 with Bobby Green, MD, president and chief medical officer, joins hosts Emeline Aviki, MD, MBA, and Stephen Schleicher, MD, MBA, to discuss his evolution as an entrepreneur in oncology care innovation and his goal of positively changing how patients experience the cancer system.
Listen
New TROPiCS-02 Data Back Sacituzumab Govitecan for Older Patients With Breast Cancer
December 9th 2023This phase 3 study investigated sacituzumab govitecan, a Trop-2–directed antibody-drug conjugate, vs treatment of physician’s choice in pretreated patients who have endocrine-resistant hormone receptor–positive/HER2-negative breast cancer, the most common form of breast cancer.
Read More
Insufficient Data, Disparities Plague Lung Cancer Risk Factor Documentation
September 24th 2023On this episode of Managed Care Cast, we speak with the senior author of a study published in the September 2023 issue of The American Journal of Managed Care® on the importance of adequate and effective lung cancer risk factor documentation to determine a patient's eligibility for screening.
Listen
Patients With RA in Remission Withdrawing From TNF Inhibition Show Flare Increases
December 8th 2023New data presented at ACR 2023 highlighted the differences in rates of flares and Boolean 2.0 remission rates compared to patients with rheumatoid arthritis who continued a tumor necrosis factor inhibitor (TNFi).
Read More