Tumour necrosis factor inhibitor monotherapy vs combination with MTX in the treatment of PsA: a systematic review of the literature
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to review the available evidence on TNF inhibitor monotherapy vs combination therapy with MTX in PsA. METHODS: A literature search was conducted up to and including October 2013 for randomized controlled trials (RCTs) and observational studies comparing TNF inhibitor monotherapy vs combination therapy with MTX in patients with PsA. Key information was extracted from the abstracts and/or full text of the articles retrieved. RESULTS: Eleven published articles and three conference abstracts were retrieved, reporting on six RCTs of four TNF inhibitors. Most RCTs found no differences in efficacy for peripheral arthritis between patients treated with or without MTX. However, the studies were not powered to answer this question. Some data suggest that concomitant MTX may reduce the progression of structural damage. No significant differences in other outcomes have been reported. Data on TNF inhibitor monotherapy vs MTX combination therapy were reported from six registries. Three registries reported that the use of concomitant MTX did not affect the efficacy of TNF inhibitor therapy. Data from three European Union registries suggest that TNF inhibitor (especially mAbs) drug survival is superior in patients taking concomitant MTX, while one Canadian registry reported no difference. CONCLUSION: Available evidence on the efficacy and safety of TNF inhibitor monotherapy vs add-on MTX therapy shows little or no improvement with combination therapy, although the use of concomitant MTX appears to prolong TNF inhibitor drug survival of mAb TNF inhibitors. Registries and observational studies have the potential to fill some of the knowledge gaps in this area.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Systematic review comparing TNF inhibitor monotherapy with combination therapy in psoriatic arthritis; uses synthesis to answer a clinical question.
It synthesizes clinical evidence about psoriasis arthritis treatment, not evidence-synthesis methodology.
Clinical systematic review of TNF inhibitors for PsA; synthesis answers a treatment question.
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".