Low awareness of the transitivity assumption in complex networks of interventions: a systematic survey from 721 network meta-analyses.

BACKGROUND: The transitivity assumption is the cornerstone of network meta-analysis (NMA). Violating transitivity compromises the credibility of the indirect estimates and, by extent, the estimated treatment effects of the comparisons in the network. The present study offers comprehensive empirical evidence on the completeness of reporting and evaluating transitivity in systematic reviews with multiple interventions. METHODS: We screened the datasets of two previous empirical studies, resulting in 361 systematic reviews with NMA published between January 2011 and April 2015. We updated our evidence base with an additional 360 systematic reviews with NMA published between 2016 and 2021, employing a pragmatic approach. We devised assessment criteria for reporting and evaluating transitivity using relevant methodological literature and compared their reporting frequency before and after the PRISMA-NMA statement. RESULTS: Systematic reviews published after PRISMA-NMA were more likely to provide a protocol (odds ratio (OR): 3.94, 95% CI: 2.79-5.64), pre-plan the transitivity evaluation (OR: 3.01, 95% CI: 1.54-6.23), and report the evaluation and results (OR: 2.10, 95% CI: 1.55-2.86) than those before PRISMA-NMA. However, systematic reviews after PRISMA-NMA were less likely to define transitivity (OR: 0.57, 95% CI: 0.42-0.79) and discuss the implications of transitivity (OR: 0.48, 95% CI: 0.27-0.85) than those published before PRISMA-NMA. Most systematic reviews evaluated transitivity statistically than conceptually (40% versus 12% before PRISMA-NMA, and 54% versus 11% after PRISMA-NMA), with consistency evaluation being the most preferred (34% before versus 47% after PRISMA-NMA). One in five reviews inferred the plausibility of the transitivity (22% before versus 18% after PRISMA-NMA), followed by 11% of reviews that found it difficult to judge transitivity due to insufficient data. In justifying their conclusions, reviews considered mostly the comparability of the trials (24% before versus 30% after PRISMA-NMA), followed by the consistency evaluation (23% before versus 16% after PRISMA-NMA). CONCLUSIONS: Overall, there has been a slight improvement in reporting and evaluating transitivity since releasing PRISMA-NMA, particularly in items related to the systematic review report. Nevertheless, there has been limited attention to pre-planning the transitivity evaluation and low awareness of the conceptual evaluation methods that align with the nature of the assumption.

Indirect comparison of pembrolizumab monotherapy versus nivolumab + ipilimumab in first-line metastatic lung cancer.

Aim: This study indirectly compared the effectiveness of pembrolizumab monotherapy versus nivolumab + ipilimumab in metastatic non-small-cell lung cancer. Materials and methods: A matching-adjusted indirect comparison was conducted using pooled individual patient data from KEYNOTE-024 and KEYNOTE-042 and published aggregate data from CheckMate 227 Part 1A, with platinum doublet chemotherapy as the anchor. Results: After matching, estimated hazard ratios (95% CI) of pembrolizumab monotherapy versus nivolumab + ipilimumab for overall survival and progression-free survival were 1.07 (0.82, 1.39) and 1.16 (0.93, 1.45), respectively. For objective response rate, the estimated risk ratio (95% CI) was 0.93 (0.71, 1.22) and the risk difference (95% CI) was -2.86%(-11.38, 5.67). Conclusion: Matching-adjusted indirect comparison results demonstrated comparable effectiveness between pembrolizumab monotherapy and nivolumab + ipilimumab as first-line therapies for metastatic non-small-cell lung cancer with PD-L1 tumor-proportion score ≥1%.

How robust are findings of pairwise and network meta-analysis in the presence of missing participant outcome data?

BACKGROUND: To investigate the prevalence of robust conclusions in systematic reviews addressing missing (participant) outcome data via a novel framework of sensitivity analyses and examine the agreement with the current sensitivity analysis standards. METHODS: We performed an empirical study on systematic reviews with two or more interventions. Pairwise meta-analyses (PMA) and network meta-analyses (NMA) were identified from empirical studies on the reporting and handling of missing outcome data in systematic reviews. PMAs with at least three studies and NMAs with at least three interventions on one primary outcome were considered eligible. We applied Bayesian methods to obtain the summary effect estimates whilst modelling missing outcome data under the missing-at-random assumption and different assumptions about the missingness mechanism in the compared interventions. The odds ratio in the logarithmic scale was considered for the binary outcomes and the standardised mean difference for the continuous outcomes. We calculated the proportion of primary analyses with robust and frail conclusions, quantified by our proposed metric, the robustness index (RI), and current sensitivity analysis standards. Cohen's kappa statistic was used to measure the agreement between the conclusions derived by the RI and the current sensitivity analysis standards. RESULTS: One hundred eight PMAs and 34 NMAs were considered. When studies with a substantial number of missing outcome data dominated the analyses, the number of frail conclusions increased. The RI indicated that 59% of the analyses failed to demonstrate robustness compared to 39% when the current sensitivity analysis standards were employed. Comparing the RI with the current sensitivity analysis standards revealed that two in five analyses yielded contradictory conclusions concerning the robustness of the primary analysis results. CONCLUSIONS: Compared with the current sensitivity analysis standards, the RI offers an explicit definition of similar results and does not unduly rely on statistical significance. Hence, it may safeguard against possible spurious conclusions regarding the robustness of the primary analysis results.

Pembrolizumab+chemotherapy versus atezolizumab+chemotherapy+/-bevacizumab for the first-line treatment of non-squamous NSCLC: A matching-adjusted indirect comparison.

OBJECTIVES: Multiple immunotherapy and chemotherapy combinations are approved for the management of advanced NSCLC which have not been directly compared in randomized clinical trials. This study indirectly compared the effectiveness of pembrolizumab + chemotherapy versus atezolizumab + chemotherapy+/-bevacizumab for previously untreated non-squamous NSCLC patients without EGFR/ALK aberrations. MATERIALS AND METHODS: A matching-adjusted indirect comparison (MAIC) was conducted using individual patient data (IPD) from KEYNOTE-021 Cohort G (KN021 G) (pembrolizumab + carboplatin + pemetrexed; N = 59) and KEYNOTE-189 (KN189) (pembrolizumab + pemetrexed + platinum chemotherapy; N = 410) and published aggregate data from IMpower 130 (atezolizumab + carboplatin + nab-paclitaxel; N = 451) and IMpower 150 (atezolizumab + carboplatin + paclitaxel + bevacizumab; N = 356). To adjust for cross-trial differences in baseline characteristics, data from patients randomized to pembrolizumab + chemotherapy in KN021 G/KN189 were reweighted to match the baseline characteristics of patients randomized to atezolizumab + chemotherapy from IMpower 130 or atezolizumab + chemotherapy + bevacizumab from IMpower 150. Outcomes included overall survival (OS), blinded independent review-assessed progression-free survival (PFS) and objective response rate (ORR). OS and PFS follow-up were truncated to the trial with shorter follow-up. Sensitivity analyses were conducted without truncation of follow-up of OS and PFS. RESULTS: After matching for cross-trial differences, the effective sample size of pembrolizumab + chemotherapy was 428 and 389 for the IMpower 130 and IMpower 150 comparisons, respectively. The estimated HRs (95 % CIs) of pembrolizumab + chemotherapy versus atezolizumab + chemotherapy were 0.80 (0.67,0.95) and 0.79 (0.67,0.93) with regard to OS and PFS, respectively. For pembrolizumab + chemotherapy versus atezolizumab + chemotherapy + bevacizumab, the estimated HR (95 % CIs) was 0.86 (0.72,1.03) for OS and 0.81 (0.68,0.96) for PFS. For ORR, the estimated risk ratio (95 % CI) and the risk difference (95 % CI) was 0.9 (0.8,1.1) and -3.5 % (-10.0,3.1) for pembrolizumab + chemotherapy versus atezolizumab + chemotherapy, respectively, and 0.8 (0.7,0.9) and -12.2 % (-19.6,-4.8) for pembrolizumab + chemotherapy versus atezolizumab + chemotherapy + bevacizumab, respectively. Findings were consistent across sensitivity analyses for both outcomes. CONCLUSION: MAIC results showed a significantly better OS and PFS for pembrolizumab + chemotherapy compared with atezolizumab + chemotherapy and a significantly better PFS for pembrolizumab + chemotherapy compared with atezolizumab + chemotherapy + bevacizumab.

Quantifying the robustness of primary analysis results: A case study on missing outcome data in pairwise and network meta-analysis.

Conducting sensitivity analyses is an integral part of the systematic review process to explore the robustness of results derived from the primary analysis. When the primary analysis results can be sensitive to assumptions concerning a model's parameters (e.g., missingness mechanism to be missing at random), sensitivity analyses become necessary. However, what can be concluded from sensitivity analyses is not always clear. For instance, in a pairwise meta-analysis (PMA) and network meta-analysis (NMA), conducting sensitivity analyses usually boils down to examining how 'similar' the estimated treatment effects are from different re-analyses to the primary analysis or placing undue emphasis on the statistical significance. To establish objective decision rules regarding the robustness of the primary analysis results, we propose an intuitive index, which uses the whole distribution of the estimated treatment effects under the primary and alternative re-analyses. This novel index is compared to an objective threshold to infer the presence or lack of robustness. In the case of missing outcome data, we additionally propose a graph that contrasts the primary analysis results to those of alternative scenarios about the missingness mechanism in the compared arms. When robustness is questioned according to the proposed index, the suggested graph can demystify the scenarios responsible for producing inconsistent results to the primary analysis. The proposed decision framework is immediately applicable to a broad set of sensitivity analyses in PMA and NMA. We illustrate our framework in the context of missing outcome data in both PMA and NMA using published systematic reviews.

Continuous(ly) missing outcome data in network meta-analysis: A one-stage pattern-mixture model approach.

Appropriate handling of aggregate missing outcome data is necessary to minimise bias in the conclusions of systematic reviews. The two-stage pattern-mixture model has been already proposed to address aggregate missing continuous outcome data. While this approach is more proper compared with the exclusion of missing continuous outcome data and simple imputation methods, it does not offer flexible modelling of missing continuous outcome data to investigate their implications on the conclusions thoroughly. Therefore, we propose a one-stage pattern-mixture model approach under the Bayesian framework to address missing continuous outcome data in a network of interventions and gain knowledge about the missingness process in different trials and interventions. We extend the hierarchical network meta-analysis model for one aggregate continuous outcome to incorporate a missingness parameter that measures the departure from the missing at random assumption. We consider various effect size estimates for continuous data, and two informative missingness parameters, the informative missingness difference of means and the informative missingness ratio of means. We incorporate our prior belief about the missingness parameters while allowing for several possibilities of prior structures to account for the fact that the missingness process may differ in the network. The method is exemplified in two networks from published reviews comprising a different amount of missing continuous outcome data.

Pattern-mixture model in network meta-analysis of binary missing outcome data: one-stage or two-stage approach?

BACKGROUND: Trials with binary outcomes can be synthesised using within-trial exact likelihood or approximate normal likelihood in one-stage or two-stage approaches, respectively. The performance of the one-stage and the two-stage approaches has been documented extensively in the literature. However, little is known about how these approaches behave in the presence of missing outcome data (MOD), which are ubiquitous in clinical trials. In this work, we compare the one-stage versus two-stage approach via a pattern-mixture model in the network meta-analysis using Bayesian methods to handle MOD appropriately. METHODS: We used 29 published networks to empirically compare the two approaches concerning the relative treatment effects of several competing interventions and the between-trial variance (τ2), while considering the extent and level of balance of MOD in the included trials. We additionally conducted a simulation study to compare the competing approaches regarding the bias and width of the 95% credible interval of the (summary) log odds ratios (OR) and τ2 in the presence of moderate and large MOD. RESULTS: The empirical study did not reveal any systematic bias between the compared approaches regarding the log OR, but showed systematically larger uncertainty around the log OR under the one-stage approach for networks with at least one small trial or low event risk and moderate MOD. For these networks, the simulation study revealed that the bias in log OR for comparisons with the reference intervention in the network was relatively higher in the two-stage approach. Contrariwise, the bias in log OR for the remaining comparisons was relatively higher in the one-stage approach. Overall, bias increased for large MOD. For these networks, the empirical results revealed slightly higher τ2 estimates under the one-stage approach irrespective of the extent of MOD. The one-stage approach also led to less precise log OR and τ2 when compared with the two-stage approach for large MOD. CONCLUSIONS: Due to considerable bias in the log ORs overall, especially for large MOD, none of the competing approaches was superior. Until a more competent model is developed, the researchers may prefer the one-stage approach to handle MOD, while acknowledging its limitations.

A Matching-Adjusted Indirect Comparison of Pembrolizumab + Chemotherapy vs. Nivolumab + Ipilimumab as First-Line Therapies in Patients with PD-L1 TPS ≥1% Metastatic NSCLC.

BACKGROUND: In the absence of head-to-head trials, this study indirectly compared the effectiveness of pembrolizumab + chemotherapy vs nivolumab + ipilimumab for the first-line treatment of metastatic stage IV NSCLC patients with PD-L1 tumor proportion score (TPS) ≥1%. METHODS: An anchored matching-adjusted indirect comparison (MAIC) was conducted using pooled individual patient data (IPD) from the ITT population in KEYNOTE-021G, KEYNOTE-189 and KEYNOTE-407 (n = 816) and published aggregate data of nivolumab + ipilimumab from CheckMate 227 Part 1A (n = 793). To adjust for cross-trial differences in baseline characteristics, data from KEYNOTE-021G/KEYNOTE-189/KEYNOTE-407 were re-weighted to match the baseline characteristics of CheckMate 227 Part 1A. Outcomes included OS, PFS and ORR. Base case analyses were restricted to patients with PD-L1 TPS ≥1%, with sub-group analyses in PD-L1 TPS ≥50% and 1-49%. RESULTS: The estimated HR (95% CI) of pembrolizumab + chemotherapy vs nivolumab + ipilimumab was 0.80 (0.59,1.09) and 0.53 (0.41,0.68) for OS and PFS, respectively. For ORR, the estimated risk ratio was 1.8 (1.3,2.4) for pembrolizumab + chemotherapy vs nivolumab + ipilimumab and the risk difference was 25.5% (15.0,36.0). PD-L1 TPS ≥50% and 1-49% sub-groups showed an OS HR of 0.89 (0.58,1.36) and 0.68 (0.46,1.01), respectively. CONCLUSION: These MAIC results suggest that pembrolizumab + chemotherapy leads to a greater clinical benefit vs nivolumab + ipilimumab in patients with PD-L1 TPS ≥1% across multiple endpoints.

Comparison of exclusion, imputation and modelling of missing binary outcome data in frequentist network meta-analysis.

BACKGROUND: Missing participant outcome data (MOD) are ubiquitous in systematic reviews with network meta-analysis (NMA) as they invade from the inclusion of clinical trials with reported participant losses. There are available strategies to address aggregate MOD, and in particular binary MOD, while considering the missing at random (MAR) assumption as a starting point. Little is known about their performance though regarding the meta-analytic parameters of a random-effects model for aggregate binary outcome data as obtained from trial-reports (i.e. the number of events and number of MOD out of the total randomised per arm). METHODS: We used four strategies to handle binary MOD under MAR and we classified these strategies to those modelling versus excluding/imputing MOD and to those accounting for versus ignoring uncertainty about MAR. We investigated the performance of these strategies in terms of core NMA estimates by performing both an empirical and simulation study using random-effects NMA based on electrical network theory. We used Bland-Altman plots to illustrate the agreement between the compared strategies, and we considered the mean bias, coverage probability and width of the confidence interval to be the frequentist measures of performance. RESULTS: Modelling MOD under MAR agreed with exclusion and imputation under MAR in terms of estimated log odds ratios and inconsistency factor, whereas accountability or not of the uncertainty regarding MOD affected intervention hierarchy and precision around the NMA estimates: strategies that ignore uncertainty about MOD led to more precise NMA estimates, and increased between-trial variance. All strategies showed good performance for low MOD (<5%), consistent evidence and low between-trial variance, whereas performance was compromised for large informative MOD (> 20%), inconsistent evidence and substantial between-trial variance, especially for strategies that ignore uncertainty due to MOD. CONCLUSIONS: The analysts should avoid applying strategies that manipulate MOD before analysis (i.e. exclusion and imputation) as they implicate the inferences negatively. Modelling MOD, on the other hand, via a pattern-mixture model to propagate the uncertainty about MAR assumption constitutes both conceptually and statistically proper strategy to address MOD in a systematic review.

Comparative effectiveness of secukinumab and etanercept in biologic-naïve patients with psoriatic arthritis assessed by matching-adjusted indirect comparison.

OBJECTIVE: Matching-adjusted indirect comparison (MAIC) can be used to assess the comparative effectiveness of two treatments indirectly using data from randomized placebo-controlled trials. This MAIC assessed the comparative effectiveness of secukinumab (an anti-interleukin-17A) and etanercept (a tumor necrosis factor inhibitor) in a target population of biologic-naïve patients with psoriatic arthritis (PsA). METHODS: Individual patient data pooled from FUTURE 2 (NCT01752634), FUTURE 3 (NCT01989468), and FUTURE 5 (NCT02404350) (secukinumab: 150 mg, n=458 and 300 mg, n=461) were matched to data from the population in the NCT00317499 trial (etanercept 25 mg, n=101) using MAIC methodology, by adjusting for clinical and demographic baseline characteristics. Recalculated outcomes from FUTURE 2, 3, and 5 (150 mg, effective sample size (ESS) post-matching=104; 300 mg, ESS=75; and placebo, ESS=159) were compared with the NCT00317499 trial. Pairwise comparisons using odds ratios (ORs) were performed for the American College of Rheumatology (ACR) 20, 50, and 70 response criteria at week 12 (placebo-adjusted) and week 24 (non-placebo-adjusted). RESULTS: At week 12, there were no significant differences in ACR responses between secukinumab and etanercept. There was no significant difference between secukinumab 150 mg and etanercept at week 24 with respect to ACR 20 and 50 response rates; however, ACR 70 response rates were higher for secukinumab 150 mg (OR (95% confidence interval (CI)): 4.48 (2.01-9.99), p<0.001). ACR 20, 50, and 70 response rates were higher with secukinumab 300 mg than with etanercept at this time point (OR (95% CI): ACR 20, 3.28 (1.69-6.38), p<0.001; ACR 50, 1.90 (1.04-3.50), p=0.038; and ACR 70, 3.56 (1.51-8.40), p=0.004). CONCLUSION: In this MAIC, secukinumab was associated with higher ACR 20 and 50 (secukinumab 300 mg) and 70 (secukinumab 150 mg and 300 mg) response rates at week 24 than etanercept in biologic-naïve patients with active PsA, whereas no significant difference was observed in the short-term at week 12.

Participants' outcomes gone missing within a network of interventions: Bayesian modeling strategies.

OBJECTIVES: To investigate the implications of addressing informative missing binary outcome data (MOD) on network meta-analysis (NMA) estimates while applying the missing at random (MAR) assumption under different prior structures of the missingness parameter. METHODS: In three motivating examples, we compared six different prior structures of the informative missingness odds ratio (IMOR) parameter in logarithmic scale under pattern-mixture and selection models. Then, we simulated 1000 triangle networks of two-arm trials assuming informative MOD related to interventions. We extended the Bayesian random-effects NMA model for binary outcomes and node-splitting approach to incorporate these 12 models in total. With interval plots, we illustrated the posterior distribution of log OR, common between-trial variance (τ2 ), inconsistency factor and probability of being best per intervention under each model. RESULTS: All models gave similar point estimates for all NMA estimates regardless of simulation scenario. For moderate and large MOD, intervention-specific prior structure of log IMOR led to larger posterior standard deviation of log ORs compared to trial-specific and common-within-network prior structures. Hierarchical prior structure led to slightly more precise τ2 compared to identical prior structure, particularly for moderate inconsistency and large MOD. Pattern-mixture and selection models agreed for all NMA estimates. CONCLUSIONS: Analyzing informative MOD assuming MAR with different prior structures of log IMOR affected mainly the precision of NMA estimates. Reviewers should decide in advance on the prior structure of log IMOR that best aligns with the condition and interventions investigated.

Matching-adjusted indirect comparison: secukinumab versus infliximab in biologic-naive patients with psoriatic arthritis.

Aim: To compare secukinumab with infliximab in biologic-naive patients with psoriatic arthritis using matching-adjusted indirect comparison. Patients & methods: Individual patient baseline data for secukinumab were matched to published aggregate data for infliximab by key baseline characteristics, with matching weights determined by logistic regression, and used to recalculate American College of Rheumatology (ACR) responses for secukinumab, for comparison with infliximab. Results: There were no differences in outcomes between secukinumab and infliximab at weeks 6/8 and 14/16. At weeks 24 and 54/52, ACR 20 responses were higher with secukinumab 150 mg than infliximab. At week 54/52, ACR 20/50 responses were higher for secukinumab 300 mg than infliximab. Conclusion: In the mid to long term, patients receiving secukinumab were more likely to achieve ACR 20/50 responses than those receiving infliximab.

Botulinum Toxins Type A (Bont-A) in the Management of Lower Limb Spasticity in Children: A Systematic Literature Review and Bayesian Network Meta-analysis.

BACKGROUND: Botulinum neurotoxins type A (BoNT-As) are used in pediatric lower limb spasticity, which affects more than 2.5 million children worldwide. Botulinum neurotoxins type-A improve active function and delay musculoskeletal complications. The objective of this analysis was to evaluate the efficacy and safety of abobotulinumtoxinA versus other botulinum neurotoxins type A in pediatric spasticity, in the absence of head-to-head evidence. METHODS: A systematic literature review was conducted to identify relevant randomized controlled trials. The evidence base was synthesized with Bayesian network meta-analyses. Outcomes analyzed included Modified Ashworth Scale, Tardieu Scale (TS) spasticity grade, and Goal Attainment Scale (standard mean difference only) at 12 weeks postinjection, and adverse events occurring during study periods. RESULTS: Thirty-eight studies were identified, 10 of which met inclusion criteria for quantitative synthesis. On Modified Ashworth Scale, abobotulinumtoxinA 15 U/kg/leg was significantly more efficacious than onabotulinumtoxinA 4 U/kg/leg (-0.99 [-1.34, -0.64]) and onabotulinumtoxinA 4 U/kg/leg+casting (-0.81 [-1.16, -0.46]) and numerically better than onabotulinumtoxinA 8 U/kg (-0.40 [-0.67, -0.14]). AbobotulinumtoxinA 10 U/kg/leg was significantly more efficacious than onabotulinumtoxinA 4 U/kg/leg (±casting). On Goal Attainment Scale, abobotulinumtoxinA 15 U/kg/leg and 10 U/kg/leg were significantly more efficacious than onabotulinumtoxinA 12 U/kg/leg. On Tardieu Scale spasticity grade, abobotulinumtoxinA was comparable to other treatments. AbobotulinumtoxinA demonstrated adverse event rates comparable to all doses of onabotulinumtoxinA. CONCLUSIONS: In pediatric lower limb spasticity, abobotulinumtoxinA offered significant or numerical efficacy advantages on tone (Modified Ashworth Scale) and functional outcomes (Goal Attainment Scale), and comparable efficacy on Tardieu Scale spasticity grade. AbobotulinumtoxinA was comparable to onabotulinumtoxinA on tolerability. Results should be interpreted in the context of heterogeneity and sparsity of the evidence base.

Comparative effectiveness of secukinumab and adalimumab in ankylosing spondylitis as assessed by matching-adjusted indirect comparison.

OBJECTIVE: Matching-adjusted indirect comparison was used to assess the comparative effectiveness of secukinumab 150 mg and adalimumab 40 mg in biologic-naïve patients with ankylosing spondylitis (AS) for up to 1 year. METHODS: Pooled individual patient data from the secukinumab arms of MEASURE 1 (NCT01358175) and MEASURE 2 (NCT01649375) trials (n=197) were matched against the ATLAS (NCT00085644) adalimumab population (n=208). Logistic regression analysis was used to determined weights to match for age, sex, Bath AS Functional Index, C-reactive protein levels, and previous tumor necrosis factor inhibitor therapy. Recalculated Assessment of SpondyloArthritis International Society (ASAS) 20 and 40 responses at weeks 8, 12, 16, 24, and 52 from MEASURE 1/2 (effective sample size=120) were compared with those of ATLAS. Anchored (placebo-adjusted) comparisons were possible until week 12, and unanchored (non-placebo-adjusted) comparisons were necessary thereafter. RESULTS: For placebo-anchored ASAS 20 and 40 comparisons up to week 12, there were no differences between secukinumab and adalimumab. For unanchored comparisons at week 16, ASAS 20 was higher for secukinumab [odds ratio 1.60 (95% confidence interval, 1.01-2.54); p=0.047]; at week 24, ASAS 20 and 40 were higher for secukinumab [1.76 (1.11-2.79); p=0.017 and 1.79 (1.14-2.82); p=0.012, respectively]; and at week 52, ASAS 40 was higher for secukinumab [1.54 (1.06-2.23); p=0.023] than for adalimumab. CONCLUSION: There were no differences observed in placebo-adjusted ASAS 20 and 40 responses up to 12 weeks between secukinumab- and adalimumab-treated patients with ankylosing spondylitis. After week 12, secukinumab demonstrated signs of greater improvement in non-placebo-adjusted ASAS 20 and 40 responses than adalimumab.