Table 5 Predicting MTX failure Predictor Number of patients Female gender n (%) Age diagnosis (years) Age MTX onset (years) Symptom duration prior to MTX (months) RF positive (yes/no) ARA criteria (yes/no) SJC TJC 28 SJC 28 TJC Baseline CRP* Baseline DAS28* Baseline HAQ SE positive (yes/no){ Steroids (yes/no) 1 year MTX fail 59 (25) 45 (76) 58.9 (45.4–70.5) 58.9 (47.8–71) 6.24 (3.6–13.18) 25 (45) 27 (46) 5 (2–10) 8 (2–15) 3 (2–8) 5 (1–9) 10 (2–26) 3.71 (3.1–4.9) 1.5 (0.625–2) 40 (78) 11 (18.6) Still on 231 (75) 147 (64) 59.3 (48.3–69) 60 (50.8–69.8) 6.27 (3.75–12.68) 94 (41) 121 (52) 4 (1–11) 5 (1–15) 4 (1–9) 3 (0–10) 13 (5–26) 3.9 (3.0–4.8) 1 (0.5–1.625) 126 (64) 39 (16.9) p Value 0.07 0.8 0.82 0.72 0.84 0.36 0.76 0.19 0.89 0.46 0.38 0.99 0.04 0.05 0.75 2 years MTX fail 95 68 (72) 59.3 (52–68.2) 59.9 (52.2–68.8) 6.28 (3.64–13.04) 40 (44) 45 (47) 5 (2–10) 6 (1–16) 3 (1–8) 4 (0–9) 10 (3–28) 3.7 (3.1–4.9) 1.25 (0.625–1.875) 62 (74) 28 (29) ARA, American Rheumatism Association; CRP, C-reactive protein; DAS, disease activity score (using 28 joint counts); HAQ, Health Assessment Questionnaire; MTX, methotrexate; RF, rheumatoid factor; SE, shared epitope; SJC, swollen joint count; TJC, tender joint count. *293 patients had baseline CRP available and, therefore, could have DAS28 results calculated. {260 patients had DNA samples and were successfully genotyped for SE. Extended report Still on 188 (61) 117 (62) 58.7 (46.9–69.5) 59.4 (49.1–70.5) 6.09 (3.56–14.59) 87 (46) 101 (54) 5 (1–11) 5 (1–13) 4 (1–9) 4 (0–10) 13 (5–26) 4.0 (3.0–4.8) 1 (0.5–1.625) 99 (63) 18 (10) p Value 0.1 0.88 0.95 0.66 0.95 0.3 0.79 0.35 0.83 0.73 0.86 0.69 0.1 0.1 0.001 treatment with MTX, sulfasalazine and hydroxychloroquine, whereas patients who were SE negative did equally well regardless of treatment allocation. Our results are in contrast to those of Criswell et al17 who found that patients who were SE positive were more likely to respond to MTX. Further studies are required to reconcile these apparently contradictory results. The strength of this study is that we were able to recruit an unselected cohort of patients with IP and so the results are generalisable to other unselected inflammatory arthritis cohorts. The treatment of early IP is difficult because most of the evidence base relates to patients who satisfy the American College of Rheumatology (ACR) criteria. Yet it is increasingly recognised that treatment should be started as early as possible before the ACR criteria have been satisfied, with the PROMPT (Probable rheumatoid arthritis: Methotrexate versus Placebo Treatment) study showing benefit of early introduction of MTX in patients with undifferentiated IP in terms of slowing the progression to ‘‘ACR criteria’’ RA.18 Thus it is a strength of this study that it adds to the evidence base of the efficacy of treatment in patients with undifferentiated IP. There are, however, a number of limitations. First, the measure of disease response was not based on a formal protocol but reflected physician opinion. Hence the decision to stop treatment because of inefficacy was not standardised between patients. Further, as the NOAR follow-up was based on anniversary since entry, we do not have the detailed clinical data on disease activity and drug dose; for example, at the time of stopping treatment to obtain objective data to support the decision to stop treatment. This also meant that a number of patients were Table 6 Predicting methotrexate failure excluded from the analysis either because they had already started on MTX, or did not start within 3 months of their clinical assessment. Furthermore, there are additional, unmea- sured predictors that may influence treatment response in this cohort, and hence improve the fit of the prediction models. We did not have radiographic data available on all patients and so these could not be included in the analysis. As this was a primary care based cohort of early disease, with short symptom duration, it was assumed that the prevalence of erosive disease at baseline would be low and, therefore, x-rays were not routinely taken on all patients at baseline. Despite its limitations, this study highlights that clinical and laboratory factors per se, even in combination, are relatively poor at predicting treatment response to MTX at least as judged by physician decision to stop treatment. This suggests that, first, there is no simple decision rule that could guide which patients should and should not be commenced on MTX. Secondly, given that response to treatment is unlikely to be a truly random event, there must be a number of other biomarkers, for example, not measured in this study that may influence outcome of MTX treatment. There have been several studies suggesting that polymorphisms in some of the pathways involved in the metabolism of MTX may be useful in predicting drug outcome,19 with a recent pharmacogenetic model being used to predict drug outcome in a subset of patients.20 To date, the clinical utility of such a model has still to be fully established. Further attempts to refine our ability to predict treatment response may therefore need to incorporate both additional genetic biomarkers and psychosocial factors, such as 1 year 2 years Unadjusted OR Predictor (95% CI) Adjusted OR p Value (95% CI) p Value Unadjusted OR (95% CI) Adjusted OR p Value (95% CI) p Value HAQ score 1.55 (1.05 to 2.3) 0.03 SE positive 2.02 (0.98 to 4.18) 0.05 1.47 (0.98 to 2.2) 0.06 2.5 (1.2 to 5.47) 0.02 1.35 (0.97 to 1.9) 0.08 1.62 (0.9 to 2.9) 0.1 1.34 (0.93 to 1.93) 0.1 1.75 (0.94 to 3.27) 0.08 HAQ, Health Assessment Questionnaire; SE, shared epitope. Ann Rheum Dis 2009;68:57–62. doi:10.1136/ard.2008.088237 61