Patient outcomes improve when a molecular signature test guides treatment decision-making in rheumatoid arthritis.

BACKGROUND: The molecular signature response classifier (MSRC) predicts tumor necrosis factor-ɑ inhibitor (TNFi) non-response in rheumatoid arthritis. This study evaluates decision-making, validity, and utility of MSRC testing. METHODS: This comparative cohort study compared an MSRC-tested arm (N = 627) from the Study to Accelerate Information of Molecular Signatures (AIMS) with an external control arm (N = 2721) from US electronic health records. Propensity score matching was applied to balance baseline characteristics. Patients initiated a biologic/targeted synthetic disease-modifying antirheumatic drug, or continued TNFi therapy. Odds ratios (ORs) for six-month response were calculated based on clinical disease activity index (CDAI) scores for low disease activity/remission (CDAI-LDA/REM), remission (CDAI-REM), and minimally important differences (CDAI-MID) . RESULTS: In MSRC-tested patients, 59% had a non-response signature and 70% received MSRC-aligned therapy . In TNFi-treated patients, the MSRC had an 88% PPV and 54% sensitivity. MSRC-guided patients were significantly (p < 0.0001) more likely to respond to b/tsDMARDs than those treated according to standard care (CDAI-LDA/REM: 36.0% vs 21.9%, OR 2.01[1.55-2.60]; CDAI-REM: 10.4% vs 3.6%, OR 3.14 [1.94-5.08]; CDAI-MID: 49.5% vs 32.8%, OR 2.01[1.58-2.55]). CONCLUSION: MSRC clinical validity supports high clinical utility: guided treatment selection resulted in significantly superior outcomes relative to standard care; nearly three times more patients reached CDAI remission.

Clinicians can offer rheumatoid arthritis patients many types of therapies but the response rate for each of these drugs is low. For example, within the first year of treatment, just about one-half of patients respond to the first-line drug, csDMARD. Only one-third of methotrexate-unresponsive patients will respond to the most common second-line agent, a tumor necrosis factor-α inhibitor. These low response rates present a critical challenge to treating patients. Clinicians try different cs- and b/tsDMARD and fail to quickly identify the most effective options. Then, disease will progress, irreversibly destroying patient joints, diminishing patient health-related quality of life, and increasing risks of cardiovascular disease, cancer, and death. To help clinicians quickly identify the best drugs for patients in a treat-to-target approach, a precision-medicine test was developed to identify patients unlikely to respond to tumor necrosis factor-α inhibitors. This molecular signature response classifier considers both molecular features (patient RNA-expression levels) and clinical features (e.g. body mass index, sex) to predict patient response. To evaluate the effectiveness of this test, the outcomes of patients treated with classifier-selected drugs (in a large, tested cohort) were compared with outcomes of patients treated with conventionally selected therapies (in an external cohort of electronic-health-record data). Patients treated with classifier-selected therapies were approximately three times as likely to achieve remission than were patients treated with conventionally selected drugs. These results suggest that this molecular signature response classifier is a valuable tool for more quickly identifying optimal therapies to treat rheumatoid arthritis.

Improvement in clinical disease activity index when treatment selection is informed by the tumor necrosis factor-ɑ inhibitor molecular signature response classifier: analysis from the study to accelerate information of molecular signatures in rheumatoid arthritis.

BACKGROUND: A blood-based molecular signature response classifier (MSRC) predicts non-response to tumor necrosis factor-ɑ inhibitors (TNFi) in rheumatoid arthritis (RA). RESEARCH DESIGN AND METHODS: This is an interim analysis of data collected in the Study to Accelerate Information of Molecular Signatures (AIMS) in RA from patients who received the MSRC test between September 2020 and November 2021. Absolute changes in clinical disease activity index (CDAI) scores from baseline were evaluated at 12 weeks (n = 470) and 24 weeks (n = 274). RESULTS: Predicted TNFi non-responders who received a biologic or targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD) with an alternative mechanism of action (altMOA) experienced up to 1.8-fold greater improvements in CDAI scores than those treated with a TNFi (12 weeks: 12.2 vs 8.0; p-value = 0.083; 24 weeks: 14.2 vs 7.8 p-value = 0.009). In patients with a molecular signature of non-response to TNFi in high disease activity at baseline, this corresponded to 43.2% relative improvement in achieving a lower CDAI disease activity level when likely TNFi non-responders were treated with a non-TNFi therapy (38.9% vs 55.7%). Commensurate improvements in efficiency of spend are expected when TNFi are avoided in favor of altMOA. CONCLUSIONS: RA treatment selection informed by MSRC test results improves clinical outcomes in real-world care and offers improvements in efficiency of healthcare spending.

Association of Breast Cancer Screening Behaviors With Stage at Breast Cancer Diagnosis and Potential for Additive Multi-Cancer Detection via Liquid Biopsy Screening: A Claims-Based Study.

PURPOSE: To evaluate mammography uptake and subsequent breast cancer diagnoses, as well as the prospect of additive cancer detection via a liquid biopsy multi-cancer early detection (MCED) screening test during a routine preventive care exam (PCE). METHODS: Patients with incident breast cancer were identified from five years of longitudinal Blue Health Intelligence® (BHI®) claims data (2014-19) and their screening mammogram and PCE utilization were characterized. Ordinal logistic regression analyses were performed to identify the association of a biennial screening mammogram with stage at diagnosis. Additional screening opportunities for breast cancer during a PCE within two years before diagnosis were identified, and the method extrapolated to all cancers, including those without recommended screening modalities. RESULTS: Claims for biennial screening mammograms and the time from screening to diagnosis were found to be predictors of breast cancer stage at diagnosis. When compared to women who received a screening mammogram proximal to their breast cancer diagnosis (0-4 months), women who were adherent to guidelines but had a longer time window from their screening mammogram to diagnosis (4-24 months) had a 87% increased odds of a later-stage (stages III or IV) breast cancer diagnosis (p-value <0.001), while women with no biennial screening mammogram had a 155% increased odds of a later-stage breast cancer diagnosis (p-value <0.001). This highlights the importance of screening in the earlier detection of breast cancer. Of incident breast cancer cases, 23% had no evidence of a screening mammogram in the two years before diagnosis. However, 49% of these women had a PCE within that time. Thus, an additional 11% of breast cancer cases could have been screened if a MCED test had been available during a PCE. Additionally, MCED tests have the potential to target up to 58% of the top 5 cancers that are the leading causes of cancer death currently without a USPSTF recommended screening modality (prostate, pancreatic, liver, lymphoma, and ovarian cancer). CONCLUSION: The study used claims data to demonstrate the association of cancer screening with cancer stage at diagnosis and demonstrates the unmet potential for a MCED screening test which could be ordered during a PCE.

Imaging taste responses in the fly brain reveals a functional map of taste category and behavior.

The sense of taste allows animals to distinguish nutritious and toxic substances and elicits food acceptance or avoidance behaviors. In Drosophila, taste cells that contain the Gr5a receptor are necessary for acceptance behavior, and cells with the Gr66a receptor are necessary for avoidance. To determine the cellular substrates of taste behaviors, we monitored taste cell activity in vivo with the genetically encoded calcium indicator G-CaMP. These studies reveal that Gr5a cells selectively respond to sugars and Gr66a cells to bitter compounds. Flies are attracted to sugars and avoid bitter substances, suggesting that Gr5a cell activity is sufficient to mediate acceptance behavior and that Gr66a cell activation mediates avoidance. As a direct test of this hypothesis, we inducibly activated different taste neurons by expression of an exogenous ligand-gated ion channel and found that cellular activity is sufficient to drive taste behaviors. These studies demonstrate that taste cells are tuned by taste category and are hardwired to taste behaviors.