J Res Health Sci. 22(4):. doi: 10.34172/jrhs.2022.96Original Article
Investigation of the Utility of Multivariate MetaAnalysis Methods in Estimating the Summary Dose Response Curve
Melepurakkal Sadanandan Deepthy^{ 1}, Kalesh Mappilakudy Karun^{ 2}, Kotten Thazhath Harichandrakumar^{ 1}, Narayanapillai Sreekumaran Nair^{ 1, }^{ *}
^{1}Department of Biostatistics, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
^{2}Division of Biostatistics, Malankara Orthodox Syrian Church Medical College, Kolenchery, Ernakulam, Kerala, India
*Corresponding author: Narayanapillai Sreekumaran Nair (PhD), Email: nsknairmanipal@gmail.com
Abstract
Background: Traditional metaanalyses often assess the effectiveness of different doses of the same intervention separately or examine the overall differences between intervention and placebo groups. The present study aimed to model the effect sizes obtained from different doses in multiple studies using a twostage doseresponse metaanalytic approach while taking dose variations into account.
Methods: Different doseresponse metaanalysis models using linear, quadratic, and restricted cubic spline (RCS) functions were fitted. A twostage approach utilizing multivariate metaanalysis was performed and the obtained results were compared with those of the univariate metaanalysis. A random effect doseresponse metaanalysis was performed using data from an existing systematic review on combination therapy with zonisamide and antiParkinson drugs for Parkinson’s disease. The effective or optimum dose for producing maximum response was also investigated. Moreover, a sensitivity analysis was performed by changing the knots of the RCS model.
Results: Doseresponse metaanalysis was performed using data from four doubleblinded randomized controlled trials with 724 and 309 patients with Parkinson’s disease in dose and placebo arms, respectively. The quadratic model yielded the smallest Akaike information criterion (AIC), compared to the linear and RCS models, indicating it to be the best fit for the data.
Conclusion: Compared to the traditional approach, the twostage approach could model the dosedependent effect of zonisamide on the Unified Parkinson’s Disease Rating Scale (UPRDS) part III score and predict the outcome for different doses through a single analysis.
Keywords: Doseresponse metaanalysis, Multivariate metaanalysis, Parkinson’s disease, Restricted cubic spline model, Zonisamide
Copyright
© 2022 The Author(s); Published by Hamadan University of Medical Sciences.
This is an openaccess article distributed under the terms of the Creative Commons Attribution License (
https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The doseresponse relationship is frequently investigated in clinical, epidemiological, and pharmacological studies.^{1} The effectiveness of any pharmacological intervention varies depending on the concentration of the drug administered, which makes it important to unveil and understand the doseresponse relationship. Traditional metaanalyses often assess the effectiveness of different doses of the same intervention separately or examine the overall differences between intervention and placebo groups without consideration of the dose variations.^{2} Sometimes a subgroup analysis is also performed by classifying the doses as high and low which results in the loss of information about the intermediate doses.
Doseresponse or doseeffect relationship metaanalysis overcomes this limitation by modeling the relationship between effect sizes and different doses obtained from multiple studies.^{3} More importantly, it helps to incorporate the dependency between the studyspecific effect estimates arising from the use of the same referent, compared to the conventional approach.^{2} It also helps researchers understand how the effect of an intervention varies as a function of its dose. There are two kinds of doseresponse metaanalytic approaches; namely, onestage and twostage doseresponse metaanalysis. They are used to study the shape of the doseresponse association using aggregated data from multiple studies.^{4}
In the current study, a twostage doseresponse metaanalysis was performed using data from an existing systematic review on combination therapy with zonisamide and antiParkinson drugs for Parkinson’s disease.^{5} Parkinson’s disease is a type of central nervous system ailment that causes patients to lose their balance, induces difficulty in walking, and causes a lack of coordination. Various medications, such as levodopa, safinamide, dopamine agonists, and zonisamide are used to treat Parkinson’s disease.Among them,zonisamide is also used to treat epilepsy and psychiatric disorders.^{6,7}
Results of a few primary studies conducted in Japan have shown that zonisamide combination therapy improves motor and nonmotor functions in patients with Parkinson’s disease.^{810} Although there have been few reviews and one metaanalysis about the effect of zonisamide on Parkinson’s disease, information on the doseresponse relationship is not evident in these studies.^{5,1113} The primary outcome evaluated in most of the studies was the unified Parkinson’s disease part III rating scale.^{14} It includes 14 items that examine speech, facial expression, finger and hand movements, posture, gait, and the effects of tremor, rigidity, and bradykinesia. Each item is scored from 0 to 4, where 0 indicates normal and 4 indicates severely affected. It is commonly used to assess the disease severity, progression, and response to treatment.
Secondary outcomes, such as the Unified Parkinson’s Disease Rating Scale (UPDRS) part II score, total score, wearing off time, and adverse events were also studied. The pairwise metaanalysis available in the literature only investigated the overall improvement in UPDRS part III score between the zonisamide and placebo using all doses of zonisamide.^{5}
This study aimed to demonstrate the utility of doseresponse metaanalysis with multivariate methods and compare the obtained summary results with those of a univariate metaanalysis. Doseresponse metaanalysis will also help to predict the dose at which the maximum response is achieved, compared to the traditional metaanalysis. These reasons could make doseresponse metaanalysis more clinically relevant than traditional metaanalysis. The reporting of dose response metaanalysis can be done in accordance with the Gdose (43 items) checklist for reporting dose response metaanalysis.^{15}
Methods
Before the doseresponse metaanalysis, estimates for different dose versus placebo comparisons were retrieved from individual studies. Pooled effect estimates were estimated for the different dose versus placebo comparisons. The data for this demonstration was taken from an existing systematic review on combination therapy with zonisamide and antiParkinson drugs for Parkinson’s disease.^{5}
The MetaAnalytic Framework: TwoStage DoseResponse MetaAnalysis
A statistical model for modeling the doseresponse relationship of correlated differences in mean scores of UPDRS part III with different dose variants was examined through a twostage doseresponse metaanalysis.^{3} In the first stage of the doseresponse metaanalysis, once the effect estimates and their variancecovariance structure were obtained, a doseresponse model was fitted in each study. The studyspecific regression coefficients are often obtained by fitting appropriate linear or nonlinear functions, such as Emax, quadratic, logistic, fractional polynomial, flexible piecewise linear, and restricted cubic spline (RCS). These were later combined using multivariate metaanalysis in the second stage of the study.^{1618} The RCS and quadratic models have the added advantage of flexibility and can be performed if at least three levels of quantitative exposure exist (i.e., two different doses along with placebo). Studyspecific trends were graphically plotted along with the study estimates and 95% confidence intervals (CIs). The linearity assumption was checked using Wald’s test, and a P value less than 0.05 was considered statistically significant.
Once the vector of correlated effect estimates (m_{i}) and the corresponding variancecovariance matrix (S_{i}) was obtained from each study, the studyspecific function could be defined as the following:
(1)
$${m}_{i}=f\left({z}_{i},{\beta}_{i}\right)+{\epsilon}_{i}$$
Where,
${\epsilon}_{i}\sim N\left(0,{\widehat{\Omega}}_{i}\right),\text{\hspace{0.33em}}i=1,2,\mathrm{....}n$
and
${\widehat{\Omega}}_{i}$
is the covariance matrix.
Linear, quadratic, and RCS models given below^{3} were fitted and the model that provided the lowest Akaike information criterion (AIC) was preferred.
(2)
$$1.\text{\hspace{0.33em}}Linear\text{}function:E\left[\raisebox{1ex}{${m}_{i}$}\!\left/ \!\raisebox{1ex}{${z}_{i}$}\right.\right]={\beta}_{1i}{z}_{i}$$
(3)
$$2.\text{\hspace{0.33em}}Quadratic\text{}function:E\left[\raisebox{1ex}{${m}_{i}$}\!\left/ \!\raisebox{1ex}{${z}_{i}$}\right.\right]={\beta}_{1i}{z}_{i}+{\beta}_{2i}{z}_{i}^{2}$$
(4)
$$\begin{array}{l}3.\text{\hspace{0.33em}}The\text{}RCS\text{}model\text{}with\text{}three\text{}knots\text{\hspace{0.33em}}{p}_{1},\text{\hspace{0.33em}}{p}_{2}\text{\hspace{0.33em}}and\text{\hspace{0.33em}}{p}_{3}:\\ E\left[\raisebox{1ex}{${m}_{i}$}\!\left/ \!\raisebox{1ex}{${z}_{i}$}\right.\right]={\beta}_{1i}{z}_{1i}+{\beta}_{2i}{z}_{2i}\end{array}$$
Where m_{i} is the vector of correlated effect estimates, z_{i} is the vector of doses, β_{1i} and β_{2i} are regression coefficients, z_{1} and z_{2} are the two transformations
$$\begin{array}{l}{z}_{1}=z\\ {z}_{2}=\frac{{\left(z{p}_{1}\right)}_{+}^{3}\frac{{p}_{3}{p}_{1}}{{p}_{3}{p}_{2}}{\left(z{p}_{2}\right)}_{+}^{3}+\frac{{p}_{2}{p}_{1}}{{p}_{3}{p}_{2}}{\left(z{p}_{3}\right)}_{+}^{3}}{{\left({p}_{3}{p}_{1}\right)}^{2}}\end{array}$$
(Note: the notation “ + ”, with v_{ + }= v if v ≥ 0 and v_{ + }= 0 otherwise)
The knots for the RCS model were specified at the 25^{th}, 50^{th}, and 75^{th} percentiles of the overall dose distribution. Generalized least square estimation was used to estimate the studyspecific doseresponse coefficients from m_{i}, S_{i}, and the design matrix X_{i} as follows:
$${\widehat{\beta}}_{i}={\left({X}_{i}^{T}{S}_{i}^{1}{X}_{i}\right)}^{1}\left({X}_{i}^{T}{S}_{i}^{1}{m}_{i}\right)\text{\hspace{0.33em}}and\text{\hspace{0.33em}}var\left({\widehat{\beta}}_{i}\right)={\left({X}_{i}^{T}{S}_{i}^{1}{X}_{i}\right)}^{1}$$
In the second stage, a multivariate metaanalysis was used to combine the vector of studyspecific doseresponse coefficients
$(\widehat{\beta})$
and the variancecovariance structure acquired
$({\widehat{\Omega}}_{i}={\widehat{\beta}}_{i})$
from different studies. The vector of pooled coefficients and its variance covariance matrix are given below^{1921}:
$$\widehat{\beta}={\left({\displaystyle \sum _{i=1}^{n}{w}_{i}^{*}}\right)}^{1}\left({\displaystyle \sum _{i=1}^{n}{w}_{i}^{*}{\widehat{\beta}}_{i}}\right)$$
${w}_{i}^{*}={\left(\widehat{T}+{\widehat{\Omega}}_{i}\right)}^{1}$
is the weight assigned to the m^{th} study.
$\widehat{T}$
is the between study variance covariance matrix, and
${\widehat{\Omega}}_{i}$
is the withinstudy variancecovariance matrix.
$$Var(\widehat{\beta})\approx {\left({\displaystyle \sum _{i=1}^{n}{w}_{i}^{*}}\right)}^{1}$$
The pooled doseresponse curve using
$\widehat{\beta}$
and
$Var(\widehat{\beta})$
derived through multivariate metaanalysis for a set of z dose values was provided by
$E\left[\raisebox{1ex}{$\widehat{m}$}\!\left/ \!\raisebox{1ex}{$z$}\right.\right]=f\left(Z,\widehat{\beta}\right)$
along with an approximate 95% CI:
$$E\left[\raisebox{1ex}{$\widehat{m}$}\!\left/ \!\raisebox{1ex}{$z$}\right.\right]\pm {Z}_{\raisebox{1ex}{$\alpha $}\!\left/ \!\raisebox{1ex}{$2$}\right.}\sqrt{diag\left(f{\left(Z,\widehat{\beta}\right)}^{T}Var\left(\widehat{\beta}\right)f\left(Z,\widehat{\beta}\right)\right)}$$
The results are presented as a graph using the predicted outcomes for a set of z dose values. Heterogeneity across studyspecific trends was assessed using a multivariate extension of Cochran’s Q test for heterogeneity and quantified using I^{2}. An I^{2} > 50% was considered to indicate considerable heterogeneity. The predicted responses using the models were compared to the observed pooled effect estimates for different doses versus placebo in the univariate metaanalysis. The dose at which the maximum observed response was determined. The effective doses required to produce 50% and 80% of the maximum response were also estimated. A sensitivity analysis was performed for the RCS model by specifying alternative knots at the 10^{th}, 50^{th}, and 90^{th} percentiles of the overall distribution of doses to determine how sensitive are the predicted pooled effect estimates to variations in the location of knots. All statistical analyses were carried out using dosresmeta package available in R software version 4.1.1. ^{22,23}
Results
In the current study, four clinical trials that examined the dosedependency relationship between zonisamide and UPDRS outcomes were used for analysis. The characteristics of the included trials are listed in Table 1. The sample sizes of the included studies were within the range of 136375. zonisamide doses of 0, 25, 50, 100, and 200 mg/d have been used in different studies. The pooled difference between the mean scores of intervention and placebo for UPDRS part III were found to be 1.37 (95% CI: 0.31, 2.43), 2.27 (95% CI: 1.25, 3.29), and 2.67 (95% CI: 0.73, 4.61) for 25, 50, and 100 mg/d from three, four, and two studies, respectively. Only one study investigated a dosage of 200 mg/d, which reported a reduction in UDRS part III score of 5.60 (95% CI: 1.60, 9.60).
Table 1.
Characteristics of the trials included and aggregate doseresponse data from four randomized control trials investigating the effectiveness of zonisamide in patients with Parkinson’s disease
Study ID/design

Sample size (n)

Dosage of zonisamide (mg)

UPDRS part III

Mean

SD

AD810N2021 




Double blind RCT (10 weeks)  34  200  9.2  7.92 
 36  100  6.5  8.16 
 34  50  6.4  7.80 
 32  Placebo  3.6  8.61 
Murata 2007 




Double blind RCT 12 weeks)  82  100  4.6  7.24 
 85  50  5.8  7.38 
 77  25  6.3  7.02 
 82  Placebo  2.0  7.24 
Murata 2015 




Double blind RCT (12 weeks)  121  50  3.8  5.50 
 125  25  2.0  5.59 
 129  Placebo  2.3  5.68 
Murata 2015 A 




Double blind RCT (12 weeks)  66  50  5.5  7.03 
 64  25  5.9  7.03 
 66  Placebo  2.9  7.14 
UPDRS, Unified Parkinson’s Disease Rating Scale; SD, standard deviation.
Doseresponse relationship within studies
The studyspecific predicted curves and CI (horizontal dashed lines), which were obtained using a RCS model, are shown in . Squares with vertical lines represent the mean difference in UPDRS part III score along with 95% CI for different doses in each of the studies. The RCS model was fitted with three knots specified at the 25^{th}, 50^{th}, and 75^{th} percentiles (6.25, 37.50, and 50.0 mg/d) of the overall distribution of zonisamide doses.
Figure 1.
Studyspecific difference in the mean scores of Unified Parkinson’s Disease Rating Scale part III for an increase in the dose of zonisamide. Zonisamide doses were modeled using the restricted cubic spline model. Black squares and whiskers represent the differences in mean UPDRS part III scores and their 95 % confidence intervals
Synthesis of coefficients obtained from multiple studies
The coefficient
${\widehat{\beta}}_{1}$
of linear model was estimated to be 0.025. The assumption of linearity was checked (P < 0.001) and evidence was found for the nonlinear association between the zonisamide dosage and UPDRS part III score. The coefficients of the quadratic model
${\widehat{\beta}}_{1}$
and
${\widehat{\beta}}_{2}$
were estimated to be 0.065 and 0.0003. In the pooled doseresponse metaanalysis model (RCS), the pooled difference in mean UPDRS part III motor score using 0 mg/d as a reference was 0.08z_{1 } 0.03z_{2}. The corresponding 95% CI for a set of z dose of interest is given by the following:
$$\left(0.08{z}_{1}0.03{z}_{2}\right)\pm 1.96\sqrt{0.0014{z}_{1}^{2}+0.0009{z}_{2}^{2}0.002{z}_{1}{z}_{2}}$$
Heterogeneity across studies was found to be statistically significant (Q = 17.00, P = 0.01, I^{2} = 64.7%). The RCS modelbased predicted differences in the mean score of UPDRS part III were 1.83 [95% CI: 0.21, 3.46] for 25 mg/d, 2.69 [95% CI: 1.21, 4.17] for 50 mg/d, 3.04 [95% CI: 1.69, 4.40] for 75 mg/d in comparison to placebo. The predicted differences in the mean score of UPDRS part III score using RCS, Linear, and quadratic models for different specified doses are given in Table 2. The RCS model indicated an increase in the difference in the UPDRS part III score with an increase in dose. Except for doses greater than 125 mg/d, the results were statistically significant for the RCS model, whereas the results were not significant from 125 mg/d for the quadratic model. The predicted differences using RCS and Quadratic models were close to each other for doses up to 125 mg/d. After that, the quadratic model showed a decreasing trend whereas the linear and RCS results showed an increasing trend and the results were closer to each other.
Table 2.
Observed and Predicted differences in the mean scores of the Unified Parkinson’s Disease Rating Scale part III along with 95% confidence intervals using restricted cubic spline as well as Linear and quadratic models for specified doses
Zonisamide
Dose (mg/d)

Difference in mean UPDRS part III score (95% CI)

Observed

RCS

Linear

Quadratic

25  1.37 (0.31, 2.43)  1.83 (0.21, 3.46)  0.63 (0.33, 0.93)  1.44 (0.31, 2.56) 
50  2.27 (1.25, 3.29)  2.69 (1.21, 4.17)  1.25 (0.65, 1.85)  2.48 (1.11, 3.85) 
75  No data  3.04 (1.69, 4.40)  1.88 (0.98, 2.78)  3.13 (1.69, 4.57) 
100  2.67 (0.73, 4.61)  3.40 (1.03, 5.77)  2.50 (1.31, 3.70)  3.38 (0.40, 6.36) 
125  No data  3.76 (0.08, 7.43)  3.13 (1.63, 4.63)  3.24 (2.76, 9.24) 
150  No data  4.11 (0.93, 9.16)  3.76 (1.96, 5.55)  2.71 (7.50, 12.91) 
175  No data  4.47 (1.98, 10.92)  4.38 (2.28, 6.48)  1.78 (13.72, 17.29) 
200  5.60 (1.60, 9.60)  4.83 (3.04, 12.69)  5.01 (2.61, 7.41)  0.46 (21.42, 22.34) 
AIC  No data  11.44  12.74  33.65 
${\widehat{ED}}_{50}$
 No data  36.89  99.98  30.37 
${\widehat{ED}}_{80}$
 No data  132.31  159.99  57.29 
AIC, Akaike information criterion; UPDRS, Unified Parkinson’s Disease Rating Scale; RCS, restricted cubic spline.
Among all three models, thequadratic model gave the smallest AIC = 33.65 in comparison to the other two models indicating it to be the best fit to the data. The RCS model gave an AIC = 11.44 similar to that of the linear model (AIC = 12.74). Even though a smaller AIC was obtained for the linear model, compared to the RCS model, the difference was negligible which may be due to the fewer number of dose categories in each study which may not be sufficient to detect a nonlinear relationship.
The predicted pooled doseresponse curve along with the CIs and the difference in mean UPDRS part III scores for different models are shown in . Zonisamide doses were modeled using RCSs as well as linear and quadratic functions, respectively (). The solid line represents the pooled doseresponse association between zonisamide and the difference in mean UPDRS outcome while the dashed lines represent the 95% CIs. It should be noted that the placebo group served as the reference group. The circles indicate the difference in the mean UPDRS part III scores obtained from the individual studies. The size of each circle is proportional to the precision of the estimate. The percentage of the maximum predicted effect or relative efficacy is shown on the right axis.
Figure 2.
Pooled doses response association between zonisamide and difference in means of UPDRS part III score using (a) restricted cubic spline, (b) linear, and (c) quadratic models
The results showed a significant association between increasing doses of zonisamide and the difference in the mean UPDRS part III score with the maximum response of 4.83 and 5.01 observed at x_{max} = 200 mg/d using RCS and linear models. Under the RCS model, the dose required to produce 50% and 80% of maximum response were estimated to be
${\widehat{ED}}_{50}=36.89\text{\hspace{0.33em}}mg/d$
and
${\widehat{ED}}_{80}=132.31\text{\hspace{0.33em}}mg/d$
. The
${\widehat{ED}}_{80}$
of the linear and quadratic model was estimated to be 99.98 mg/d and 30.37 mg/d. Similarly, estimated values of
${\widehat{ED}}_{80}$
for the linear and quadratic model are found to be 159.99 mg/d and 57.29 mg/d, respectively.
Sensitivity analysis
A sensitivity analysis was performed for the RCS model by specifying the knots at the 10^{th}, 50^{th}, and 90^{th} percentiles (0, 37.5, and 100.0 mg/d) of the overall distribution of the zonisamide doses. The pooled difference in means in UPDRS part III motor score using 0 mg/d as reference and the corresponding 95% CI for a set of z dose of interest was calculated using the following:
$$\left(0.064{z}_{1}0.05{z}_{2}\right)\pm 1.96\sqrt{0.0007{z}_{1}^{2}+0.0036{z}_{2}^{2}0.003{z}_{1}{z}_{2}}$$
The AIC of the RCS with alternative knots was found to be 4.09 which was higher than that of the RCS model indicating it to be less fit to the data than the RCS model with knots at 25^{th}, 50^{th}, and 75^{th} percentiles. The predicted pooled difference in means of UPDRS part III motor score using both RCS models were found to be similar, hence, less variation was observed in the shape of the curves.
Discussion
Doseresponse metaanalysis helps to estimate more comprehensive and reliable high grade evidence. According to this study, the quadratic model provided a better fit to the data. In addition, this study was the first to investigate the potential dosedependent effect of zonisamide combination therapy on the UPDRS part III score in Parkinson’s disease. The findings regarding the effect of zonisamide on UPDRS part III score were in accordance with those of a prior metaanalysis which also showed an improvement in the outcome.^{5}
Previous metaanalyses only performed a pairwise metaanalysis between the zonisamide and placebo groups. However, there are significant differences in the doses studied across different studies ranging from 0 to 200 mg/d. In addition, the differences between doses of zonisamide and placebo were not considered in the existing pairwise metaanalysis. The optimal dose for reduction in the UPDRS part III score also has not been determined. A previous metaanalysis indicated an overall reduction in the UPDRS part III score in the zonisamide group when compared to the placebo group (weighted mean difference: 2.56 [95% CI: 0.92, 4.20, P = 0.002]), whereas the current study was able to predict an improvement above this for all zonisamide doses from 45 mg/d onwards using RCS model. An improvement was observed for zonisamide doses above the threshold of 20 mg/d in the RCS model and the results were statistically significant up to 125 mg/d.
Although the doseresponse metaanalysis revealed an improvement in response to the increase in dose for linear and RCS, the quadratic model predicted initially increasing and later decreasing trends. When compared to the observed pooled responses for different doses versus placebo, the effect estimates were higher except for 200 mg for RCS and Quadratic. The CIs were wider in both RCS and quadratic models, compared to the linear model.
The
${\widehat{ED}}_{50}$
estimated using quadratic and RCS models were similar, whereas
${\widehat{ED}}_{50}$
of linear was found to be three times higher, compared to the RCS and quadratic models. Estimated values of
${\widehat{ED}}_{80}$
under linear and RCS were almost equal but were higher than that estimated under Quadratic. The present study determined the dose that yielded the maximum response. The maximum response or greatest reduction in the UPDRS part III score of the zonisamide and placebo was observed as 4.83 and 5.01, respectively, at x_{max} = 200 mg/d using RCS and linear models. In the sensitivity analysis, no substantial differences were observed in the results that were predicted using RCS models with varying knots. Since only a few studies were available, no subgroup analysis could be conducted in the present study. In addition, there were fewer dose categories in each of the studies to explore other nonlinear models. Moreover, the generalisability of the results to other populations and the longterm efficacy of zonisamide cannot be determined since all the studies were carried out in the Japanese population with a short duration of 1012 weeks.^{5}
Doseresponse metaanalysis cannot be performed if dosewise responses are not mentioned in individual studies. Moreover, studies reporting at least two nonreferent doses along with a placebo should be available to proceed with a twostage doseresponse metaanalysis. A onestage doseresponse metaanalysis can accommodate studies with a single nonreferent dose but will provide similar results to those of a twostage analysis when studies with at least two or more nonreferent doses only exist.
The present research did not include any studies with a single comparison; therefore, a twostage approach was employed. Since it has been made mandatory to register the studies in the scientific platform and provide the data in various public data depositories, the limitations mentioned above can be dealt with in future studies by obtaining the required dosewise information from the raw data.
Conclusion
Compared to the traditional approach, doseresponse metaanalysis could provide the effects of different doses of the same drug on the outcome through a single analysis. The quadratic model showed a better fit than other models with the lowest AIC value. Traditional metaanalysis has shown that zonisamide consumption results in an improvement in the UPDRS part III score. The current doseresponse metaanalysis confirmed that combination therapies of zonisamide along with antiParkinson drug could result in improvement in the UPDRS part III score. The efficacy of different doses of zonisamide on the outcome was estimated; however, the selection of the appropriate dose also required the consideration of other outcomes, such as adverse events at various doses.
Highlights
Traditional metaanalysis estimates either overall efficacy of a drug or for each dose separately.
Doseresponse metaanalysis models the dosedependent effect of the intervention on the outcome.
Efficacy of different doses of a drug on the outcome is estimated in a single analysis.
A summary curve and heterogeneity across studyspecific trends were estimated.
Results of conventional and twostage doseresponse metaanalyses were compared.
Acknowledgments
The authors would like to thank Atul Goel, Senior Resident, Department of Neurology, JIPMER, Puducherry, India for helping with this project.
Conflict of interest
There is no potential conflict of interest.
Ethical approval
The study was carried out using the data from available literature; therefore, the Ethics committee granted a waiver of consent for the study.
Funding
This study was not funded.
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