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  string(105) "Personalized dosing of golimumab based on serum drug concentrations in patients with rheumatoid arthritis"
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  string(700) "Rheumatoid arthritis (RA) constitutes a significant burden for patients and society. Tumor necrosis factor inhibitors (TNFi) are effective treatments, but some patients fail to respond. Strategies to maximize efficacy of TNFi, including golimumab, are thus needed.  Therapeutic drug monitoring (TDM) may optimize efficacy and cost-effectiveness of treatment with TNFi, as demonstrated for infliximab in the NOR-DRUM B trial. More knowledge is needed regarding the clinical utility of TDM of subcutaneous TNFi. This requires identifying the therapeutic ranges, i.e the optimal serum drug concentration for effect. The main aim of the current project is to identify the therapeutic range for golimumab."
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  string(136) "E-mail correspondence between leader of SQUEEZE project Danial Aletaha and company. We were encouraged to apply YODA for access to data."
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      string(232) "NCT00264537 - A Multicenter, Randomized, Double-blind, Placebo-controlled Trial of Golimumab, a Fully Human Anti-TNFa Monoclonal Antibody, Administered Subcutaneously, in Methotrexate-naïve Subjects with Active Rheumatoid Arthritis"
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  ["project_ext_grants"]=>
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    ["value"]=>
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    ["label"]=>
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  }
  ["project_funding_source"]=>
  string(17) "EU (Horizon 2020)"
  ["project_date_type"]=>
  string(18) "full_crs_supp_docs"
  ["property_scientific_abstract"]=>
  string(1623) "Background: Tumor necrosis factor inhibitors (TNFi), including golimumab, have greatly improved treatment of rheumatoid arthritis, but some patients fail to respond to these treatments or lose response over time. Therapeutic drug monitoring (TDM), i.e concentration-based dosing, may optimize efficacy and cost-effectiveness of treatment with TNFi. In order to validate TDM as a clinical tool, therapeutic ranges, i.e the optimal serum concentration which is both effective and safe, must be identified.

Objective: To identify the therapeutic range for golimumab.

Study design: The proposed project will apply already available data from phase III studies of golimumab to study the relationship between serum golimumab concentration and clinical effect, in order to identify the therapeutic range.

Participants: Rheumatoid arthritis patients in the treatment arms starting golimumab in phase III trials; NCT00207714, NCT00264550, NCT00264537. 

Primary and Secondary Outcome Measure(s): European Alliance of Associations for Rheumatology (EULAR) good/moderate response, change in Disease Activity Score 28 joints (DAS28) score, DAS28 improvement ≥0.6/1.2 from baseline, DAS28 remission (score <2.6) or low disease activity (score 2.6-3.2), tender joint count, swollen joint count, change in C-reactive protein (CRP), American College of Rheumatology (ACR) 70, 50, 20 responses (70, 50, 20 % improvement from baseline).

Statistical analysis: Exploratory analyses of the association between serum drug levels and disease activity, including both graphical and regression based techniques. "
  ["project_brief_bg"]=>
  string(3159) "Rheumatoid arthritis (RA) is a chronic immune-mediated inflammatory disease characterized by symmetric inflammation of the peripheral joints [1]. RA constitutes a significant burden for the individual patient and incurs substantial direct and indirect costs on society [2]. Tumor necrosis factor inhibitors (TNFi), including golimumab, have revolutionized the treatment of RA, but not all patients respond adequately [3, 4]. Strategies to maximize treatment efficacy of TNFi treatment are thus needed. Therapeutic drug monitoring (TDM), refers to measurements of blood concentrations to guide individual dose adjustments, which may optimize efficacy and cost-effectiveness of treatment with TNFi [5, 6]. Methods for assessment of serum drug concentrations are available for use in clinical practice. Observational studies have shown associations between serum drug levels and effectiveness and also revealed considerable inter-individual variation in serum drug levels for TNFi, including golimumab, indicating both under- and overexposure [7-9]. Development of anti-drug antibodies (ADAb) is a major reason for low drug levels and lack of effectiveness of TNFi [6].



TDM of TNFi is a topic of great interest among clinicians treating patients with immune-mediated inflammatory diseases, including rheumatologists and gastroenterologists. The interest in TDM has been further spiked by the two randomized clinical Norwegian Drug Monitoring (NOR-DRUM) trials, conducted by our research group, both published in JAMA [10, 11]. NOR-DRUM B demonstrated that TDM leads to better outcomes in the maintenance phase of treatment with the TNFi infliximab across patients with immune-mediated inflammatory diseases. However, more knowledge is needed regarding the clinical utility of TDM of subcutaneous TNFi [12].



The SQUEEZE project is a European research consortium investigating personalized medicine for RA. The project is funded by EU (Horizon 2020), headed by Daniel Aletaha, Medical University of Vienna. https://squeeze-project.eu/. Work package 6 of the SQUEEZE project entails maximizing benefit of biologic disease-modifying antirheumatic drugs, such as TNFi, by TDM. To validate the use of TDM, therapeutic ranges, i.e the optimal serum drug concentration for effect, must first be identified. For golimumab, the therapeutic range remains unclear and current data is based on small observational studies [9, 13]. 

Data from dose finding studies and phase III trials represent a unique opportunity to identify the therapeutic range as well as the effect of dose adjustments on serum drug concentrations. By facilitating personalized treatment with TNFi, the proposed research has potential to improve treatment and quality of life for a large group of patients with RA.



Our project group has a solid track record in TDM research, including assessment of observational data to develop therapeutic ranges, as well as conducting clinical trials, and participation in international expert groups on TDM of biologic drugs. Our group thus has the necessary competence and resources to further develop this field."
  ["project_specific_aims"]=>
  string(756) "Primary aim: To identify the therapeutic range for golimumab. 

Secondary aims: 

•	To assess the influence of age, gender, body-weight/BMI, smoking habits, disease activity, concomitant methotrexate and anti-drug antibodies (ADAb) on serum levels and effectiveness of golimumab.



•	To assess the effect of different doses and dose adjustments on serum levels of golimumab.



Hypotheses:

•	There exists a concentration-effect relationship for golimumab and a therapeutic range can be identified

•	Patients, disease and treatment characteristics influence the relationship between serum golimumab concentration and effect

•	Serum drug levels are dependent on dose in a predictable manner"
  ["project_study_design"]=>
  array(2) {
    ["value"]=>
    string(5) "other"
    ["label"]=>
    string(5) "Other"
  }
  ["project_study_design_exp"]=>
  string(197) "Individual trial analyses. In addition, data on serum golimumab concentration and outcome measures from the three trials (NCT00207714, NCT00264550, NCT00264537) may be pooled if deemed appropriate."
  ["project_purposes"]=>
  array(2) {
    [0]=>
    array(2) {
      ["value"]=>
      string(56) "new_research_question_to_examine_treatment_effectiveness"
      ["label"]=>
      string(114) "New research question to examine treatment effectiveness on secondary endpoints and/or within subgroup populations"
    }
    [1]=>
    array(2) {
      ["value"]=>
      string(5) "other"
      ["label"]=>
      string(5) "Other"
    }
  }
  ["project_purposes_exp"]=>
  string(222) "Identify the therapeutic range for golimumab, to be incorporated in treatment algorithms in future clinical trial examining the clinical utility of concentration-based dosing (i.e TDM) of golimumab in rheumatoid arthritis."
  ["project_software_used"]=>
  array(2) {
    ["value"]=>
    string(5) "stata"
    ["label"]=>
    string(5) "STATA"
  }
  ["project_software_used_exp"]=>
  string(11) "STATA and R"
  ["project_research_methods"]=>
  string(1734) "Inclusion: All patients randomized to receive golimumab and with available serum golimumab concentration measurement in the three studies. Data from the entire Intent-to-treat population is desirable, as inclusion of patients with lack of effect, non-compliance and adverse events, etc. are necessary to study the effect of serum levels on clinical effect.

Exclusion criteria: Patients who did not receive the allocated treatment. Patients with missing serum golimumab concentration or outcome data at ≥2 time points of interest.

Time points of interest:

NCT00264550 and NCT00264537: Baseline, W12 and W 24.

NCT00207714: Baseline, W12 and W 24, Time of interval prolongation (W20), W36 and W48.



The requested data are applicable to meet our aims;

1.	All three studies include data on serum golimumab concentration, relevant covariates (age, gender, body-weight/BMI, smoking habits, disease activity, concomitant methotrexate and anti-drug antibodies), and clinical and biochemical outcome measures. These data will be used to assess the relationship between serum golimumab concentration and clinical effect, in order to identify the concentration-effect curve and hopefully the therapeutic range.

2.	In all three studies, patients received golimumab 50 or 100 mg monthly. The data are thus applicable to study the relationship of two different doses and serum concentration. Data from NCT00207714 are also applicable to assess the effect of interval prolongation from 2 to 4 weeks.

3.	Phase III trials includes data from more patients than what is usually feasible in a cohort and we consider it an advantage to use data from the phase III trial due to high validity."
  ["project_main_outcome_measure"]=>
  string(1285) "Primary outcome measures:

-European Alliance of Associations for Rheumatology (EULAR) response; no response (change in DAS28 ≤0.6), moderate response (current DAS28 <5.1 and change in DAS28 >1.2, or current DAS28 ≤5.1 and >3.2, and change in DAS28 >0.6, or current DAS28 ≤3.2 and change in DAS28 >0.6 and ≤1.2), good response (current DAS28 ≤3.2 and change in DAS28 >1.2)), 

-Disease activity score 28 joints (DAS28) improvement from baseline (continuous variable).



Secondary outcome measures: 

-DAS28 disease state (remission <2.6, low disease activity 2.6-3.2, moderate disease activity >3.2-5.1 and high disease activity >5.1)

-Change in number of tender joints (0-68) (continuous variable)

-Change in number of swollen joints (0-66) (continuous variable), 

-Change in C-reactive protein (CRP) level (mg/dL) from baseline (continuous variable)

-American College of Rheumatology (ACR) 70, 50, 20 responses (70, 50, 20 % improvement from baseline).

-Number of adverse events (including infections) (yes/no, might be classified according to MedDRa if applicable) (continuous variable). 

-Treatment discontinuation due to lack of efficacy, adverse event or other reason, yes/no, number of patients."
  ["project_main_predictor_indep"]=>
  string(129) "Serum golimumab concentration. The variable will be assessed as a continuous variable and in categories/quantiles e.g in deciles."
  ["project_other_variables_interest"]=>
  string(322) "Age, sex, race, weight, BMI, RF and ACPA-status and level IU/ml, symptom duration before

diagnosis, disease duration/diagnosis date, prior biologic DMARD use, smoking (no,

previous, current).

Golimumab dosages. 

Co-treatment methotrexate and corticosteroids; dose. 

Anti-drug antibodies."
  ["project_stat_analysis_plan"]=>
  string(3055) "The determination of a therapeutic range for golimumab serum levels will be done through a combination of receiver-operating characteristic curve analyses, explorative, and regression analysis-based techniques. The explorative analysis will, e.g., involve segmenting the range of serum levels and summarizing corresponding disease activity assessments made at the same time points. Appropriate regression analysis techniques, depending on outcome characteristics and including possibly non-parametric variants, will be used to assess and estimate the association between serum levels and disease activity. Multivariable analyses will be carried out to adjust for potential confounders (incl. age, gender, disease duration and prior use of bDMARD (Yes/No), concomitant methotrexate and body mass index). 



Assessment of how golimumab serum levels respond to changes in golimumab dosage (NCT00207714): Explorative data analysis techniques will initially be used. These will include, e.g., scatter plots of golimumab serum levels pre and post dosage changes (stratified by change magnitude), both on the original scale and of transformations (e.g. logarithmic), and scatter-(box-) plots of relative dosage change and corresponding serum level change. 



Associations between baseline variables and golimumab serum concentration will be assessed using descriptive statistics, including independent sample T-test, Mann-Whitney U tests for continuous variables or Chi-Square test for cathegorical variables.

Handling of missing data: Handling of missing data will depend on the extent of the problem. The analysis might use complete case or simple imputation techniques if the extent of missingness is minor, but multiple imputation will be employed if this is deemed not to be the case. If multiple imputation is employed, composite disease activity scores will be imputed by first imputing their component scores. Imputation models will be formed using all available observations, with the particular model type (e.g. multivariate normal model or chained equations (MICE)) determined through explorative analysis. If two substantively different models are suggested both will be implemented to assess robustness. 



Effect measures: Mean/median change 

Odds ratio (95% CI)

Regression coefficient (β), Correlation coefficient (R)



Methods to control for bias: multivariable analyses adjusting for covariates.



Strategy to maintain independence of the datasets/account for differences in study populations:

Data from different studies will initially be analyzed separately. 

If deemed appropriate, however, pooled analyses will be considered. The studies include the same outcome measures. If pooled analyses is deemed appropriate, statistical adjustments for differences in available population characteristics will be made. Study level indicators will also be included in pooled analyses, and their interaction with relevant predictors will be considered."
  ["project_timeline"]=>
  string(161) "December 2023; Estimated start of data processing.

January 2024; Estimated start of data analyses.

December 2024; Estimated publication of results."
  ["project_dissemination_plan"]=>
  string(307) "The results will be published in a peer-reviewed scientific journal with rheumatologists as target audience.

The therapeutic range identified in this study will be incorporated into future clinical trials assessing the effectiveness of TDM of TNFi such as golimumab for rheumatoid arthritis patients."
  ["project_bibliography"]=>
  string(3236) "
1. Gravallese EM, Firestein GS. Rheumatoid Arthritis – Common Origins, Divergent Mechanisms. N Engl J Med. 2023;388(6):529-42.

2. Kvien TK. Epidemiology and burden of illness of rheumatoid arthritis. Pharmacoeconomics. 2004;22(2 Suppl 1):1-12.

3. Maini R, St Clair EW, Breedveld F, Furst D, Kalden J, Weisman M, et al. Infliximab (chimeric anti-tumour necrosis factor alpha monoclonal antibody) versus placebo in rheumatoid arthritis patients receiving concomitant methotrexate: a randomised phase III trial. ATTRACT Study Group. Lancet. 1999;354(9194):1932-9.

4. Keystone E, Genovese MC, Klareskog L, Hsia EC, Hall S, Miranda PC, et al. Golimumab in patients with active rheumatoid arthritis despite methotrexate therapy: 52-week results of the GO-FORWARD study. Ann Rheum Dis. 2010;69(6):1129-35.

5. Medina F, Plasencia C, Goupille P, Ternant D, Balsa A, Mulleman D. Current Practice for Therapeutic Drug Monitoring of Biopharmaceuticals in Rheumatoid Arthritis. Ther Drug Monit. 2017;39(4):364-9.

6. Gehin JE, Goll GL, Brun MK, Jani M, Bolstad N, Syversen SW. Assessing Immunogenicity of Biologic Drugs in Inflammatory Joint Diseases: Progress Towards Personalized Medicine. BioDrugs. 2022;36(6):731-48.

7. Pouw MF, Krieckaert CL, Nurmohamed MT, van der Kleij D, Aarden L, Rispens T, et al. Key findings towards optimising adalimumab treatment: the concentration-effect curve. Ann Rheum Dis. 2015;74(3):513-8.

8. Gehin JE, Goll GL, Warren DJ, Syversen SW, Sexton J, Strand EK, et al. Associations between certolizumab pegol serum levels, anti-drug antibodies and treatment response in patients with inflammatory joint diseases: data from the NOR-DMARD study. Arthritis Res Ther. 2019;21(1):256.

9. Gehin JE, Warren DJ, Syversen SW, Lie E, Sexton J, Loli L, et al. Serum golimumab concentration and anti-drug antibodies are associated with treatment response and drug survival in patients with inflammatory joint diseases: data from the NOR-DMARD study. Scand J Rheumatol. 2021;50(6):445-54.

10. Syversen SW, Goll GL, Jørgensen KK, Sandanger Ø, Sexton J, Olsen IC, et al. Effect of Therapeutic Drug Monitoring vs Standard Therapy During Infliximab Induction on Disease Remission in Patients With Chronic Immune-Mediated Inflammatory Diseases: A Randomized Clinical Trial. Jama. 2021;325(17):1744-54.

11. Syversen SW, Jørgensen KK, Goll GL, Brun MK, Sandanger Ø, Bjørlykke KH, et al. Effect of Therapeutic Drug Monitoring vs Standard Therapy During Maintenance Infliximab Therapy on Disease Control in Patients With Immune-Mediated Inflammatory Diseases: A Randomized Clinical Trial. Jama. 2021;326(23):2375-84.

12. Krieckaert CL, van Tubergen A, Gehin JE, Hernández-Breijo B, Le Mélédo G, Balsa A, et al. EULAR points to consider for therapeutic drug monitoring of biopharmaceuticals in inflammatory rheumatic and musculoskeletal diseases. Ann Rheum Dis. 2022.

13. Kneepkens EL, Plasencia C, Krieckaert CL, Pascual-Salcedo D, van der Kleij D, Nurmohamed MT, et al. Golimumab trough levels, antidrug antibodies and clinical response in patients with rheumatoid arthritis treated in daily clinical practice. Ann Rheum Dis. 2014;73(12):2217-9.
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