Treatment Switch Patterns and Healthcare Costs in Biologic-Naive Patients with Psoriatic Arthritis
Bibliographic record
Abstract
We compared treatment switch patterns and healthcare costs among biologic-naive patients with psoriatic arthritis (PsA) who initiated apremilast or biologics. 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. 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). Biologic-naive patients with PsA who initiated apremilast had switch rates similar to biologic users and significantly lower healthcare costs, regardless of treatment switching. Psoriatic arthritis (PsA) is a chronic inflammatory disease that affects an estimated 30% of psoriasis patients who use systemic therapy. Symptoms of PsA, such as joint swelling and tenderness, can be painful and disabling and may worsen quality of life. PsA can also impart a substantial economic burden. Treatment for moderate to severe PsA often involves the use of systemic oral medications (e.g., conventional systemic treatments such as methotrexate or targeted systemic treatments such as apremilast) or biologic therapy given by injection or infusion. Because PsA symptoms and responses to treatment can vary, patients may switch treatments over time. More research is needed to better understand how switching treatments affects healthcare costs among patients starting treatment with apremilast or a biologic for PsA. This study compared treatment switching and healthcare costs among patients with PsA who had never been treated with a biologic and who started treatment with apremilast or a biologic for PsA. Rates of treatment switching at 12 months were similar for patients starting treatment with apremilast versus those starting a biologic. Patients starting treatment with apremilast had significantly lower total healthcare costs compared with those starting a biologic, even if they later switched to a biologic. Healthcare costs calculated per patient per month (PPPM) were also lower with apremilast versus biologics, driven by lower PPPM pharmacy costs. These findings suggest that starting treatment with apremilast may be an effective and cost-effective strategy for managing PsA, even for patients who later switch to a biologic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".