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Integrating imaging and biomarker assessment to better define psoriatic arthritis and predict response to biologic therapy.

ABSTRACT: The treatment options for PsA have substantially expanded over the last decade. Approximately 40% of patients will not respond to first-line anti-TNF-α therapies. There is limited data to help clinicians select the most appropriate biologic therapy for PsA patients, including guidance for decisions on biologic therapy switching. In this review we will examine the current understanding of predictors of response to treatment. Imaging technology has evolved to allow us to better study psoriatic disease and define disease activity, including synovitis and enthesitis. Enthesitis is implicated in the pathogenesis, diagnosis and prognosis of PsA. It appears to be a common thread among all of the various PsA clinical presentations. Enthesitis mainly manifests as tenderness, which is difficult to distinguish from FM, chronic pain and mechanically associated enthesopathy, and it might be relevant for understanding the apparent 40% failure of existing therapy. Excess adipose tissue makes if more difficult to detect joint swelling clinically, as many PsA patients have very high BMIs. Integrating imaging and clinical assessment with biomarker analysis could help to deliver stratified medicine in PsA and allow better treatment decision making. This could include which patients require ongoing biologic therapy, which class of biologic therapy that should be, and who alternatively requires management of non-inflammatory disease.

SUBMITTER: Elliott A

PROVIDER: S-EPMC8709569 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:INTRODUCTION:We compared treatment switch patterns and healthcare costs among biologic-naive patients with psoriatic arthritis (PsA) who initiated apremilast or biologics. METHODS:A 1:2 propensity score match was used to adjust administrative claims data for adults initiating apremilast or biologics from January 1, 2014, to September 30, 2016, for possible selection bias. Patients had at least 12 months of pre- and post-index continuous enrollment in the Optum Clinformatics™ Data Mart database. Outcomes included switch frequency, days to switch, adherence on index treatment, and healthcare costs (total and per patient per month). Switch rate was defined as the proportion of patients who switched to a new treatment after initiation of the index treatment, and days to switch was calculated as the days between initiation of the index treatment and initiation of the new treatment. Adherence was calculated using the proportion of days covered and the medication possession ratio. The t test and chi-square, Kaplan-Meier, and Wilcoxon rank-sum tests were used to evaluate differences between the cohorts. RESULTS:Patient characteristics and switch rates were similar between the matched apremilast (n?=?170) and biologic (n?=?327) cohorts. After matching, patient characteristics were similar between the matched cohorts. The 12-month switch rates were similar for patients initiating apremilast versus those on biologics (17.7% vs. 25.1%, P?=?0.06). This trend was similar at 6 months (7.7% vs. 13.2%, P?=?0.07) and 18 months (24.4% vs. 29.3%, P?=?0.33). Regardless of treatment switching, 12-month total healthcare costs were lower with apremilast versus biologics (all: $28,423 vs. $41,178, P?<?0.0001; switched: $39,803 vs. $51,517, P?=?0.0040; did not switch: $25,984 vs. $37,717, P?<?0.0001). CONCLUSIONS:Biologic-naive patients with PsA who initiated apremilast had switch rates similar to biologic users and significantly lower healthcare costs, regardless of treatment switching.

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Integrating imaging and biomarker assessment to better define psoriatic arthritis and predict response to biologic therapy.

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