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

Nair SC, Welsing PM, Choi IY, Roth J, Holzinger D, Bijlsma JW, van Laar JM, Gerlag DM, Lafeber FP, Tak PP - PLoS ONE (2016)

Bottom Line: We also investigated how the predictive effect of MRP8/14 was modified by drug type.Rheumatoid factor positivity, functional disability (a higher HAQ), and previous use of a TNF-inhibitor decreased the probability of response.Prediction 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Rheumatology and Clinical Immunology, University Medical Center, Utrecht, The Netherlands.

ABSTRACT

Objectives: Measurement 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.

Methods: Baseline 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.

Results: The 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.

Conclusions: Prediction 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.

Show MeSH

Related in: MedlinePlus

Algorithm for personalized treatment of RA patients indicated for biological treatment.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4814133&req=5

pone.0152362.g001: Algorithm for personalized treatment of RA patients indicated for biological treatment.

Mentions: The theoretical optimal treatment choice was defined based on the expected probability (‘chance’) of response to (both) TNF-inhibitors and the expected probability of response to rituximab for an individual patient. If no distinction between drug types was present using the algorithm (i.e. probability for response to TNF-inhibitors and rituximab both ‘low’, ‘moderate’ or ‘high’), treatment decisions should be made solely by the treating physician together with the patient (‘no recommendation’). Fig 1 represents the treatment algorithm and the number of patients per specific treatment advice according to this algorithm in our patient cohort.


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

Nair SC, Welsing PM, Choi IY, Roth J, Holzinger D, Bijlsma JW, van Laar JM, Gerlag DM, Lafeber FP, Tak PP - PLoS ONE (2016)

Algorithm for personalized treatment of RA patients indicated for biological treatment.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4814133&req=5

pone.0152362.g001: Algorithm for personalized treatment of RA patients indicated for biological treatment.
Mentions: The theoretical optimal treatment choice was defined based on the expected probability (‘chance’) of response to (both) TNF-inhibitors and the expected probability of response to rituximab for an individual patient. If no distinction between drug types was present using the algorithm (i.e. probability for response to TNF-inhibitors and rituximab both ‘low’, ‘moderate’ or ‘high’), treatment decisions should be made solely by the treating physician together with the patient (‘no recommendation’). Fig 1 represents the treatment algorithm and the number of patients per specific treatment advice according to this algorithm in our patient cohort.

Bottom Line: We also investigated how the predictive effect of MRP8/14 was modified by drug type.Rheumatoid factor positivity, functional disability (a higher HAQ), and previous use of a TNF-inhibitor decreased the probability of response.Prediction 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Rheumatology and Clinical Immunology, University Medical Center, Utrecht, The Netherlands.

ABSTRACT

Objectives: Measurement 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.

Methods: Baseline 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.

Results: The 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.

Conclusions: Prediction 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.

Show MeSH
Related in: MedlinePlus