The increase in erythrocyte mean corpuscularvolume by methotrexate is potentiated byhydroxychloroquine and is an early indicator ofclinical response in rheumatoid arthritis

ABSTRACT

Background/AimsRheumatologists are facing a significant challenge in the managementof early rheumatoid arthritis (RA) due to limitations placed onoutpatient visits during the COVID-19 pandemic. Frequent clinicalassessments of disease activity are recommended during implementation of the treat to target strategy to achieve remission. A biomarkerindicating response to methotrexate during the early phase of therapycould complement clinical examination. Methotrexate increaseserythrocyte mean corpuscular volume (MCV), which is measuredroutinely, prompting us to investigate whether changes in MCV couldact as an early indicator of response.MethodsPatients with early RA who were started on methotrexate therapy wereincluded from two independent cohorts. The larger cohort (discoverycohort, n = 655) was used to build the model and the second cohort(validation cohort, n = 225) was applied to test the prediction of themodel. Conventional statistical, and machine learning approacheswere adopted to identify key determinants that influence the potentialrelationship between MCV and clinical response, defined as attainment of remission or low disease activity, at six months after startingmethotrexate. ResultsA LASSO penalised logistic regression model was built with thediscovery cohort [area under the receiver operating characteristics(AUROC) curve = 0.76], where change of MCV from three months[Odds ratio (OR) 1.53 (95% CI 1.38-1.70)], concomitant use ofhydroxychloroquine [OR 2.16 (95% CI 1.52 - 3.07, p < 0.001)], andseropositivity [OR 1.83 (95% CI 1.12 - 3.03, p = 0.02)] were associatedwith favourable methotrexate response [accuracy 81% (95% CI 76%-86%) of the model testing against discovery model]. Different machinelearning classification methods were applied. Random forest exhibitedthe maximum accuracy and AUROC (89%, and 86%, respectively),confirming the above three predictors as the most significant. Twolatent classes (class 1 smaller MCV increase and class 2 greater MCVincrease) were identified based on the MCV changes over six months.Class 1 had fewer responders and a lower number of patients onhydroxychloroquine compared to class 2. The earliest time point ofsignificant difference of MCV between responders and non-responders was three months [mean difference 1.43 (95% CI 0.57-2.3)].Combination hydroxychloroquine and methotrexate caused the greatest increase in MCV with a difference between responders and nonresponders at 2 months. Change of MCV at three months showedAUROC of 0.75 to predict treatment response to the combination ofmethotrexate and hydroxychloroquine at six months with an optimalcut-point of MCV 3.5 fL (95% CI 3.5-3.6) with 71% sensitivity and75%, specificity.ConclusionOur data provides mechanistic insight into the synergistic clinicalbenefit of concomitant hydroxychloroquine with methotrexate, boosting the rise in erythrocyte MCV which could serve as an earlybiomarker of treatment response.