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INFECTIONS ASSOCIATED WITH BIOLOGIC THERAPY: A CLINICAL META-ANALYSIS STUDY

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INFECTIONS ASSOCIATED WITH BIOLOGIC THERAPY: A CLINICAL META-ANALYSIS STUDY

Anjali Nayak, Rahul Semwal, Pritish Kumar Varadwaj and Imlimaong Aier *

Department of Bioinformatics and Applied Sciences, Indian Institute of Information Technology-Allahabad, Prayagraj, Uttar Pradesh, India.

ABSTRACT: With the popularity of biologics, treatment for several inflammatory diseases has improved significantly. Biologics are a group of drugs obtained from biological sources that primarily function by suppressing part of the host immune system. However, this process comes at a cost, as it has been reported that the use of biologics carry a major risk in the form of tuberculosis. To verify this claim, a meta-analysis of biologic therapy vs. placebo therapy was designed to test biologics of different inflammatory diseases and check for tuberculosis as their side effect. This test included psoriasis, rheumatoid arthritis, psoriatic arthritis, ankylosing spondylitis, Crohn’s disease, and ulcerative colitis. It was found that biologics used in treating these diseases were mainly responsible for the spread of tuberculosis as a side effect. By mining different databases for literature mentioning biologics that qualify clinical trials and checking for heterogeneity for each study, primary measures were tested for each disease to determine the spread of tuberculosis when treated with these compounds. Meta-analyses were conducted for the study of each disease separately. It was found that for ankylosing spondylitis, Crohn’s disease, psoriasis, psoriatic arthritis, rheumatoid arthritis, and ulcerative colitis  the null hypothesis Hο:µ=0 can be rejected. All primary measures showed statistically significant results for the spread of tuberculosis infection. Therefore, it can be concluded that biologics used to treat these inflammatory diseases may be spreading infections in the form of tuberculosis.

Keywords: Biologics, Tuberculosis, Inflammatory disease, Meta-analysis

INTRODUCTION: Biologics are a group of drugs developed in the early 1980’s that are obtained from biological sources which primarily function by suppressing part of the host immune system 1. Biologic compounds are heavily used to diagnose, prevent, and treat human diseases and inflammatory conditions.

Biologics vary from traditional pharmaceutical drugs in various aspects, such as size, heterogeneity, and characterization 2. Thus, biologics development is costly and difficult due to intensive engineering and manufacturing requirements.

However, biologics remain effective and are the preferred therapeutic mode when treating severe diseases. One of the most successful and growing classes of biologics is monoclonal antibodies, proteins secreted by white blood cells that protect the body from foreign invaders. Whenever pathogens express antigens, the antibody immediately triggers an immune response which helps the body ward off the invader. Similar to antibodies, therapeutic monoclonal antibodies are produced from living organisms and engineered to work against a particular antigen concerning the disease 3. Due to the precision during engineering, therapeutic monoclonal antibodies often produce results similar to the human immune response when combating antigens. Due to the growing use of new immune-modulating therapies, comprehending the infectious complications associated with it is even more important, mainly the risk of tuberculosis and herpes zoster 4, 5. In this study, the aim was to identify the association of these agents with different infections through meta-analysis. Many immune-modulating drugs are still spreading infections in patients and are untested. Thus, the main objective was to target biologics that could cause tuberculosis as the side effect for different diseases. For this study, literature published between 2009 and 2021 were selected from PUBMED, EMBASE and Cochrane central library.

MATERIALS AND METHODS:

Extraction of Data, Selection and Characteristics of Studies: The data were collected from clinical trial organization website (clinicaltrial.org) with the help of specific keywords “ankylosing spondylitis”, “Crohn’s disease”, “adalimumab”, “psoriasis”, “infliximab”, “etanercept”, “ulcerative colitis”, “rheumatoid arthritis”, “psoriatic arthritis” containing placebo-controlled study. The titles and abstract of each study for each disease were inspected for the criteria mentioned above. The selection criteria based on which the studies were included were that the selected studies should be completed, the involved treatment should be the biologics causing tuberculosis as side effect compared to the placebo, and that the patients included in the studies should have the diseases selected for this study. Exclusion criteria was set based on certain conditions, such as the patient should not have active tuberculosis, hepatitis B or hepatitis C, or have previous anti-TNF therapy. The patient should not have any history of demyelinating disease, multiple sclerosis or cancer. After applying these criteria the number of studies selected were 8 in ankylosing spondylitis, 6 in Crohn’s disease, 7 in psoriasis, 8 in psoriatic arthritis, 5 in rheumatoid arthritis, 6 in ulcerative colitis. The baseline characteristics of patients were studied. Total 4392 patients of ankylosing spondylitis out of 8 studies 6, 7, 8, 9, 10, 11, 12, 13, 2992 patients of Crohn’s disease out of 6 studies 14, 15, 16, 17, 18, 2648 patients of Psoriasis out of 7 studies 19, 20, 21, 22, 23, 24, 25, 3046 patients of Psoriatic Arthritis out of 8 studies 26, 27, 28, 29, 30, 31, 32, 33, 1176 patients of Rheumatoid Arthritis out of 5 studies 34, 35, 36, 37, 38, 1487 patients of Ulcerative Colitis out of 6 studies 39, 40, 41, 42, 43, 44. The heterogeneity of studies was checked using χ2 and Ӏ2 index statistics. Funnel plot was used for the efficacy measure of publication bias.

The required data were extracted from various studies and divided into two groups; experiment group (biological therapy) and the control group (placebo therapy) for meta-analysis; the baseline characteristics are tabulated in Table 1. The data extracted were the name of the study, number of patients, year, age, study design, and biologics level. The primary endpoint measures were that the biological therapy should favor experiments that indicate the possibility of tuberculosis as a side effect in these diseases' biologics.

TABLE 1: BASELINE CHARACTERISTICS OF PATIENTS WITH ANKYLOSING SPONDYLITIS, CROHN’S DISEASE, PSORIASIS, PSORIATIC ARTHRITIS, RHEUMATOID ARTHRITIS AND ULCERATIVE COLITIS

Disease Study No. of patients Year Age (Years) Study design Therapy Period Dosage Regimen Intervention
Ankylosing spondylitis Abbott 315 2011 42.2 (11.57) Double blind 12 weeks 40 mg/week Adalimumab
Wyeth 566 2012 40.76 (11.86) Double blind 16 weeks 50 mg/week Etanercept
Centocor Inc. 356 2013 39.3 (12.06) Double blind 24 weeks 100 mg/4 weeks Golimumab
Pfizer 1715 2015 43.9 (12.9) Cohort 52 weeks 50mg/week Etanercept
Novartis 60 2015 42.8 (9.88) Double blind 28 weeks 0.1mg/kg/3 weeks AIN457
AbbVie 789 2013 49.3 (13.3) Case-only 13 month -- Humira
Celgene Corp. 490 2019 44.7 (12.18) Double blind 24 weeks 30 mg /week Apremilast
Merck & Sharp & Dohme Corp 101 2019 44.4 (12.9) Open label 12 months 50 mg/month GLM
Crohn’s disease Otsuka Ph. 235 2009 40.9 (12.8) Double blind 12 weeks 10 sessions Adacolumn
UCB Pharma 539 2011 37.67 (12.19) Double blind 26 weeks 400mg/2 weeks CertolizumabPegol
UCB Pharma 40 2015 31.7 (9.7) Open label 6 weeks 400mg(5 doses 4-weekly) CertolizumabPegol
Abbott 188 2011 13.6 (2.49) Double blind 52 weeks 40 mg/week Adalimumab
Janssen Biotech 297 2015 36.3 (12.96) Double blind 200 weeks 5mg/kg/8 weeks Infliximab
AbbVie 1693 2014 35.5 (11.7) Cohort 24 weeks -- Humira
Psoriasis Wyeth 720 2010 45.03 (11.85) Open label 12 weeks 50 mg twice weekly Etanercept
Wyeth 69 2013 45.84 (11.57) Open label 24 weeks 50 mg/week Etanercept
Abbott 147 2011 44.2 (12.82) Open label 24 weeks 80 mg/week Adalimumab
Pfizer 197 2012 96 Double blind 12 weeks 15 mg twice daily CP-690,550
Pfizer 171 2015 49.08 (13.96) Open label 52 weeks 50 mg/week Etanercept
AbbVie 500 2014 500 Prospective 12 months -- Adalimumab
Celgene Corp. 844 2016 46.0 (12.95) Double blind 16 weeks 30 mg twice daily Apremilast
 

 

 

 

 

 

Psoriatic arthritis

 Wyeth 753 2009 46.52 (11.40) Double blind 12 weeks 50 mg weekly Etanercept
Centocor Inc. 146 2013 48.7 (10.97) Double blind 12 weeks 90 mg/week Ustekinumab
Bristol Myers Squibb 170 2012 52 Double blind 169-729 days -- Abatacept
Novartis 42 2015 47.0 (10.2) Double blind 10 mg/kg on day 1 and 22 169 days AIN457
UCB Pharma 409 2016 47.6 (11.4) Double blind 400mg twice weekly 48 weeks CertolizumabPegol
Celgene Corp. 504 2016 50.4 (11.66) Double blind 30 mg twice daily 5 years Apremilast
Novartis 606 2016 552 Double blind 150 mg 24 weeks Secukinumab
Eli lilly& company 417 2017 49.52 (11.87) Double blind 160 mg of 2 SC injections 24 weeks Ixekizumab
Rheumatoid arthritis Abbott 619 2011 402 Double blind 52 weeks 40 mg / week Adalimumab
Novartis 80 2012 46.9 (16.22) Double blind 12 weeks 600 mg on day 1,15,43 Canakinumab
Incyte Corp. 50 2015 54.9 (11.23) Double blind 28 days 50 mg once daily INCB018424
Abbott 334 2012 54.0 (13.15) Double blind 52 weeks 40 mg SC/ week Adalimumab
Mitsubishi Tanabe Pharma Corp. 93 2014 27 Double blind 12 weeks 100 mg twice daily MP-435+Methotrexate
Ulcerative colitis Centocor Inc. 60 2013 13.4 (3.10) Open label 54 weeks 5 mg/kg every 12 weeks Infliximab
Valeant Ph. Int,Inc. 410 2014 43.6 (13.6) Double blind 8 weeks 9mg every day+3 Entocort Budesonide-MMX
Valeant Ph. Int,Inc. 489 2014 42.7 (12.8) Double blind 8 weeks 9 mg every day+2 Asacol Budesonide-MMX
Pfizer 195 2013 110 Double blind 8 weeks 15 mg twice daily CP-690,550
AbbVie 273 2014 42.7 (14.38) Double blind 221 weeks 160 mg on day 1,80 mg at week 2, 40 mg /week from 4 to 50 Adalimumab
GW Research Ltd 60 2015 43.77(13.90) Double blind 10 weeks 1-5 capsules twice daily GWP42003

Statistical Analysis: Meta-analysis was performed for assessing between the treatment group and control group. Odds ratio and confidence interval were graphically represented with the help of forest plots, while funnel plots deputed publication biases. Radial and QQ normal plots were used to represent numerical values such as angle and for showing the normal distribution of studies.

Heterogeneity was calculated using χ2 and Ӏ2 index statistics, the effect size measurement using odds ratio, and the confidence interval, odds ratio, and p-value were calculated for individual study. R software was used for statistical analysis and metafor package 45 was used to calculate the estimated result. With the help of the studies collected, biological therapy was compared against placebo treatment.

It was seen that the result favors experiments showing tuberculosis as a side effect in the biologics using the metafor package. The tool makes use of various parameters, which are described as follows. Effect size, which is a computable determination of robustness of occurrence. Escalc function was used to calculate the effect size or outcome measure. The result was yi (observed value of the effect size or outcome measure in the studies) and vi (corresponding sampling variance) for each disease. Odds ratio (OR) was calculated with the help of Mantel-Haenszel Method, which is a process that creates an evaluation of an association between an exposure and an outcome after modifying for or taking stagger into account. The formula for OR can be represented as

Or (MH) = a × d / t/ c × b / t

In which a and c are the number of events and total of experiments, b and d are the number of events and total of control, t is the total of all study. 95% confidence interval was used for this analysis, where confidence interval (CI) is a type of interval approximation of a population. If an equivalent hypothesis test is performed, the confidence level accompanies the significance level, i.e. a 95% confidence interval indicates a significance level of 0.05. P-value is the probability of acquiring a result uniform to or maximum than what is actually noticed when the null hypothesis is true. Z-value (absolute value) shows the distance between the raw score and the population means in standard deviation units. μ and σ are the mean and standard deviation of the population, respectively.

These parameters were calculated for studies of each diseases separately. forest() function was used to create the forest plot in R. Forest plot is the graphical representation of a meta-analysis which is generally escorted by a table with a list of authors and year of the studies which are taken in doing the meta-analysis.

A funnel plot, a scatter plot of treatment effect against a measure of study precision, was used to check biasness and systematic heterogeneity. When a symmetrical funnel shaped appear from a courteous data set, it is accounted that there are no publication biases. Funnel function was used to see the biasness in R. Heterogeneity was present in the selected studies, so a fixed effect model was used. Besides these, radial plots, which is a method to evaluate the stability of discovered result that have varying precisions was used to plot inverse of standard errors on horizontal axis against the individual discovered result systemized by their respective standard errors on vertical axis (i.e., yi=√vi) in fixed effect model 42. Q-Q normal plots were also generated, which display the theoretical quantiles of a normal distribution on the horizontal axis against the observed quantiles of the externally systemized residuals on the vertical axis 42.

RESULTS:

Ankylosing Spondylitis: Biologic therapy comparison was done with placebo therapy. It was seen that the result favors the experiment as compared to placebo [OR=0.8962, 95%CI=0.83-0.97, P-value>0.005] Fig. 1A. heterogeneity was calculated [χ2=21.53, Ӏ2=64.28%]. No such publication bias is seen Fig. 1B. Radial plot plots the value of numeric as angle of radians Fig. 1C. Also, the QQ plot shows that the data is normally distributed Fig.1D.

 

FIG. 1: (A) FOREST PLOT, (B) FUNNEL PLOT, (C) RADIAL PLOT AND (D) QQ PLOT FOR ANKYLOSING SPONDYLITIS

Crohn’s disease: Biologic therapy comparison was done with placebo therapy. The result was seen to favor the experiment as compared to the placebo [OR=0.82, 95%CI=0.76-0.89, P-value <0.0001]. Fig. 2A. Heterogeneity was calculated [χ2=122.29, Ӏ2=96.71%]. No such publication bias is seen Fig. 2B. Radial plot plots the value of numeric as angle of radians Fig. 2C. Also, the QQ plot shows that the data is normally distributed Fig. 2D.

FIG. 2: (A) FOREST PLOT, (B) FUNNEL PLOT, (C) RADIAL PLOT AND (D) QQ PLOTFOR ANKYLOSING SPONDYLITIS CROHN’S DISEASE

Psoriasis: Biologic therapy comparison was done with placebo therapy. It was seen that the result favors experiment as compared to placebo [OR=0.72, 95% CI=0.65-0.79, P-value<0.0001] Fig. 3A. Heterogeneity was calculated [χ2=21.68, Ӏ2=70.04%]. No such publication bias is seen Fig. 3B. Radial plot plots the value of numeric as angle of radians Fig. 3C. Also, the QQ plot shows that the data is normally distributed Fig. 3D.

 

FIG. 3: (A) FOREST PLOT, (B) FUNNEL PLOT, (C) RADIAL PLOT AND (D) QQ PLOT FOR ANKYLOSING SPONDYLITIS PSORIASIS

Psoriatic Arthritis: Biologic therapy comparison was done with placebo therapy. It was seen that the result favors the experiment as compared to placebo [OR=0.77, 95% CI=0.68-0.87, P-value<0.0001] Fig. 4A. Heterogeneity was calculated [χ2=3.10, Ӏ2=0%]. No such publication bias is seen Fig. 4B. Radial plot plots the value of numeric as angle of radians Fig. 4C. Also, the QQ plot shows that the data is normally distributed Fig. 4D.

FIG. 4: (A) FOREST PLOT, (B) FUNNEL PLOT, (C) RADIAL PLOT AND (D) QQ PLOT FOR ANKYLOSING SPONDYLITIS PSORIATIC ARTHRITIS

Rheumatoid Arthritis: Biologic therapy comparison was done with placebo therapy. It was seen that the result favors the experiment as compared to placebo [OR=0.65, 95% CI=0.53-0.79, P-value<0.0001] Fig. 5A. Heterogeneity was calculated [χ2=11.29, Ӏ2=37.61%]. No such publication bias is seen Fig. 5B. Radial plot plots the value of numeric as angle of radians Fig. 5C. Also, the QQ plot shows that the data is normally distributed Fig. 5D.

FIG. 5: (A) FOREST PLOT, (B) FUNNEL PLOT, (C) RADIAL PLOT AND (D) QQ PLOT FOR RHEUMATOID ARTHRITIS

Ulcerative Colitis: Biologic therapy comparison was done with placebo therapy. It was seen that the result favors experiment as compared to placebo [OR=0.45, 95% CI=0.36-0.56, P-value<0.0001] Fig. 6A. Heterogeneity was calculated [χ2=12.05, Ӏ2=0%]. No such publication bias is seen Fig. 6B. Radial plot plots the value of numeric as angle of radians Fig. 6C. Also, the QQ plot shows that the data is normally distributed Fig. 6D.

FIG. 6: (A) FOREST PLOT, (B) FUNNEL PLOT, (C) RADIAL PLOT AND (D) QQ PLOT FOR ULCERATIVE COLITIS

CONCLUSION: A meta-analysis of biological therapy vs. placebo therapy is done for disease like ankylosing spondylitis, Crohn’s disease, psoriasis, rheumatoid arthritis, psoriatic arthritis, ulcerative colitis with different study group of each disease to see the side effect caused by the biologics of these diseases. After meta-analysis, it can be seen that the result follows the experiment which can be concluded that the biologics of each disease gives side effect of tuberculosis. End-point measures for each diseases is estimated. The study is grouped as biologic therapy and placebo therapy.

A comparison between both groups gave a statistically significant result. The P-value for each endpoint measures ankylosing spondylitis (P>0.005), Crohn’s disease (P<0.0001), psoriasis (P<0.0001), psoriatic arthritis (P<0.0001), rheumatoid arthritis (P<0.0001), ulcerative colitis (P<0.0001) which is less than 0.05.

Publication bias was also checked with the help of a funnel plot. No such publication bias was found in each disease. This meta-analysis might contain many limitations due to search strategy applied, inclusion and exclusion criteria of studies and publication bias. Different protocols were developed to extract data from studies and analyze those data. But a vigorous strategy is applied for meta-analysis and it will help in fortune for clinical trial in biologics giving tuberculosis as side effects.

The prominence of this study was to find the side effects that can be caused by the biologics of diseases like, ankylosing spondylitis, Crohn’s disease, psoriasis, rheumatoid arthritis, psoriatic arthritis, ulcerative colitis. Finally, a meta-analysis of a clinical trial is applied, showing that the biologics have side effects. Therefore, it can be concluded that the biologics of diseases like ankylosing spondylitis, Crohn’s disease, psoriasis, rheumatoid arthritis, psoriatic arthritis, ulcerative colitis give tuberculosis as side effects.

ACKNOWLEDGEMENT: The authors acknowledge the Department of Bioinformatics & Applied Sciences, Indian Institute of Information Technology, Allahabad, for providing a computing facility. The authors thank Prof. S.P. Mishra for sharing his expertise upon consultation.

CONFLICTS OF INTEREST: The authors have no conflict of interest.

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    How to cite this article:

    Nayak A, Semwal R, Varadwaj PK and Aier I: Infections associated with biologic therapy: a clinical meta- analysis study. Int J Pharm Sci & Res 2023; 14(5): 2532-40. doi: 10.13040/IJPSR.0975-8232.14(5).2532-40.

    All © 2023 are reserved by International Journal of Pharmaceutical Sciences and Research. This Journal licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.

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IJPSR

Anjali Nayak, Rahul Semwal, Pritish Kumar Varadwaj and Imlimaong Aier *

Department of Bioinformatics and Applied Sciences, Indian Institute of Information Technology-Allahabad, Prayagraj, Uttar Pradesh, India.

imliaier@gmail.com

05 September 2022

29 October 2022

24 April 2023

10.13040/IJPSR.0975-8232.14(5).2532-40

01 May 2023

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