Evidence map›Paper›PMID 27029006›Full record

ArticlePloS one2016

A Personalized Approach to Biological Therapy Using Prediction of Clinical Response Based on MRP8/14 Serum Complex Levels in Rheumatoid Arthritis Patients.

S C Nair, P M J Welsing, I Y K Choi, J Roth, D Holzinger, J W J Bijlsma, J M van Laar, D M Gerlag, F P J G Lafeber, P P Tak

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Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

S C NairDepartment of Rheumatology and Clinical Immunology, University Medical Center, Utrecht, The Netherlands.
P M J WelsingDepartment of Rheumatology and Clinical Immunology, University Medical Center, Utrecht, The Netherlands.
I Y K ChoiDivision of Clinical Immunology and Rheumatology, Academic Medical Center/University of Amsterdam, Amsterdam, the Netherlands.
J RothInstitute of Immunology, University Hospital Muenster, Muenster, Germany.
D HolzingerDepartment of Pediatric Rheumatology and Immunology, University Children's Hospital Muenster, Muenster, Germany.
J W J BijlsmaDepartment of Rheumatology and Clinical Immunology, University Medical Center, Utrecht, The Netherlands.
J M van LaarDepartment of Rheumatology and Clinical Immunology, University Medical Center, Utrecht, The Netherlands.
D M GerlagDivision of Clinical Immunology and Rheumatology, Academic Medical Center/University of Amsterdam, Amsterdam, the Netherlands.
F P J G LafeberDepartment of Rheumatology and Clinical Immunology, University Medical Center, Utrecht, The Netherlands.
P P TakDivision of Clinical Immunology and Rheumatology, Academic Medical Center/University of Amsterdam, Amsterdam, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesMeasurement of MRP8/14 serum levels has shown potential in predicting clinical response to different biological agents in rheumatoid arthritis (RA). We aimed to develop a treatment algorithm based on a prediction score using MRP8/14 measurements and clinical parameters predictive for response to different biological agents.

methodsBaseline serum levels of MRP8/14 were measured in 170 patients starting treatment with infliximab, adalimumab or rituximab. We used logistic regression analysis to develop a predictive score for clinical response at 16 weeks. MRP8/14 levels along with clinical variables at baseline were investigated. We also investigated how the predictive effect of MRP8/14 was modified by drug type. A treatment algorithm was developed based on categorizing the expected response per drug type as high, intermediate or low for each patient and optimal treatment was defined. Finally, we present the utility of using this treatment algorithm in clinical practice.

resultsThe probability of response increased with higher baseline MRP8/14 complex levels (OR = 1.39), differentially between the TNF-blockers and rituximab (OR of interaction term = 0.78), and also increased with higher DAS28 at baseline (OR = 1.28). Rheumatoid factor positivity, functional disability (a higher HAQ), and previous use of a TNF-inhibitor decreased the probability of response. Based on the treatment algorithm 80 patients would have been recommended for anti-TNF treatment, 8 for rituximab, 13 for another biological treatment (other than TNFi or rituximab) and for 69 no recommendation was made. The predicted response rates matched the observed response in the cohort well. On group level the predicted response based on the algorithm resulted in a modest 10% higher response rate in our cohort with much higher differences in response probability in individual patients treated contrary to treatment recommendation.

conclusionsPrediction of response using MRP8/14 levels along with clinical predictors has potential in personalizing treatment for RA patients starting biological anti-rheumatic treatment, and might increase cost-effectiveness.

Indexed as

AdalimumabAdultAgedAntirheumatic AgentsArthritis, RheumatoidATP-Binding Cassette TransportersBiomarkersCalgranulin BFemaleHumansImmunosuppression TherapyInfliximabMaleMiddle AgedPrecision MedicineRituximabABCC11 protein, humanAdalimumabAntirheumatic AgentsATP-Binding Cassette TransportersBiomarkersCalgranulin BInfliximabRituximab

Identifiers

PMID27029006
PMCPMC4814133

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.