pith. sign in

arxiv: 2510.15762 · v2 · submitted 2025-10-17 · 📊 stat.AP

Incorporating estimands into meta-analyses of clinical trials

Antonio Remiro-Az\'ocar , Pepa Polavieja , Emmanuelle Boutmy , Alessandro Ghiretti , Lise Lotte Nystrup Husemoen , Khadija Rerhou Rantell , Tatsiana Vaitsiakhovich , David M. Phillippo
show 4 more authors
Jay J. H. Park Helle Lynggaard Robert Bauer Antonia Morga
This is my paper

Pith reviewed 2026-05-18 05:53 UTC · model grok-4.3

classification 📊 stat.AP
keywords estimandsmeta-analysisintercurrent eventsclinical trialsheterogeneityhealth technology assessmentnetwork meta-analysisevidence synthesis
0
0 comments X

The pith

Different target estimands at the meta-analytical level make explicit the intercurrent event strategies driving heterogeneity in clinical trial results.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper proposes a pragmatic framework for incorporating estimands into meta-analyses of clinical trials. This approach systematically identifies and addresses sources of quantitative heterogeneity that arise from how intercurrent events such as treatment discontinuation or rescue medication are handled. The authors apply the framework to a network meta-analysis comparing semaglutide and dulaglutide in type 2 diabetes, contrasting a treatment policy strategy with a hypothetical strategy. The method complements the PICO framework to improve the external validity of pooled estimates for health technology assessment. It also strengthens communication among stakeholders about the precise objectives of evidence synthesis.

Core claim

By specifying different target estimands at the meta-analytical level, the source of heterogeneity due to the intercurrent event strategy becomes explicit, allowing clearer interpretation of differences in results and enhancing the applicability of the pooled estimates to healthcare decision-making.

What carries the argument

The estimand framework, specifically its strategies for intercurrent events such as treatment policy versus hypothetical strategies, applied consistently at the meta-analytical level to distinguish contributions to heterogeneity.

Load-bearing premise

Different estimand strategies for intercurrent events can be consistently defined and applied across trials in a meta-analysis even without subject-level data from the individual studies.

What would settle it

A re-analysis of the same network meta-analysis dataset using subject-level data that shows the treatment policy and hypothetical strategies cannot be applied uniformly across trials, resulting in inconsistent or uninterpretable differences in the pooled estimates.

read the original abstract

The estimand framework is increasingly established to pose research questions in confirmatory clinical trials. In evidence synthesis, the uptake of estimands has been modest, and the PICO (Population, Intervention, Comparator, Outcome) framework is more often applied. While PICOs and estimands have overlapping elements, the estimand framework explicitly considers different strategies for intercurrent events. We propose a pragmatic framework for the use of estimands in meta-analyses of clinical trials, highlighting the value of estimands to systematically identify and mitigate key sources of quantitative heterogeneity, and to enhance the applicability or external validity of pooled estimates. Focus is placed on the role of strategies for intercurrent events, within the specific context of meta-analyses for health technology assessment. We apply the estimand framework to a network meta-analysis of clinical trials, comparing the efficacy of semaglutide versus dulaglutide in type 2 diabetes. We explore the impact of a treatment policy strategy for treatment discontinuation or initiation of rescue medication versus a hypothetical strategy for the corresponding intercurrent events. The specification of different target estimands at the meta-analytical level allows us to be explicit about the source of heterogeneity, the intercurrent event strategy, driving any potential differences in results. We advocate for the integration of estimands into the planning of meta-analyses, while acknowledging that potential challenges exist in the absence of subject-level data. Estimands can complement PICOs to strengthen communication between stakeholders about what evidence syntheses seek to demonstrate, and to ensure that the generated evidence is maximally relevant to healthcare decision-makers.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper proposes a pragmatic framework for incorporating the estimand framework into meta-analyses of clinical trials, with emphasis on using different strategies for intercurrent events (e.g., treatment policy versus hypothetical) to make sources of quantitative heterogeneity explicit and to improve the external validity of pooled estimates for health technology assessment. It illustrates the approach via a network meta-analysis comparing semaglutide versus dulaglutide in type 2 diabetes, exploring how choice of intercurrent-event strategy affects results, and advocates integrating estimands alongside PICO to strengthen communication with decision-makers while noting challenges when subject-level data are unavailable.

Significance. If the framework can be operationalized reproducibly from aggregate data, it would help meta-analysts and HTA bodies be more transparent about what target population and intercurrent-event handling a synthesis is actually estimating, thereby clarifying whether observed heterogeneity is substantive or artifactual. The semaglutide–dulaglutide example is a timely case given the importance of discontinuation and rescue in diabetes trials, but the manuscript provides only high-level description of the impact exploration.

major comments (2)
  1. [Application to semaglutide vs dulaglutide NMA] The central claim—that specifying different target estimands at the meta-analytic level isolates the intercurrent-event strategy as the driver of heterogeneity—requires that hypothetical strategies can be consistently defined and estimated from published summary statistics alone. The manuscript does not supply an explicit, reproducible mapping (e.g., the conditional outcome distributions or modeling assumptions needed to impute outcomes under a hypothetical strategy of no discontinuation/rescue) from the aggregate data used in the NMA.
  2. [Abstract and application section] The abstract and application section describe exploration of treatment-policy versus hypothetical strategies but report no quantitative results, confidence intervals, or sensitivity analyses showing how the pooled estimates or heterogeneity metrics actually change under each strategy. Without these, it is not possible to evaluate whether the estimand choice materially affects conclusions or merely restates the same data under different labels.
minor comments (2)
  1. [Methods] Clarify in the methods whether the NMA was re-run under each estimand or whether the same summary statistics were simply re-interpreted; the current description leaves this ambiguous.
  2. [Application section] Add a table or figure that tabulates the specific intercurrent-event strategies applied to each trial in the network, including any trial-specific assumptions required for the hypothetical arm.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments, which help clarify the scope and limitations of our proposed framework. We agree that operationalizing estimands from aggregate data requires care and that the application section is primarily illustrative. Below we respond point by point to the major comments.

read point-by-point responses

  1. Referee: [Application to semaglutide vs dulaglutide NMA] The central claim—that specifying different target estimands at the meta-analytic level isolates the intercurrent-event strategy as the driver of heterogeneity—requires that hypothetical strategies can be consistently defined and estimated from published summary statistics alone. The manuscript does not supply an explicit, reproducible mapping (e.g., the conditional outcome distributions or modeling assumptions needed to impute outcomes under a hypothetical strategy of no discontinuation/rescue) from the aggregate data used in the NMA.

    Authors: We agree that a fully reproducible numerical implementation of a hypothetical strategy from aggregate data alone would require explicit conditional distributions or modeling assumptions that are not provided in the published summaries. Our manuscript is deliberately pragmatic and acknowledges this limitation in the absence of subject-level data. The central claim is not that hypothetical strategies can be estimated without assumptions, but that explicitly specifying the estimand at the meta-analytic level makes the intercurrent-event strategy (and any associated assumptions) transparent as a potential source of heterogeneity. We will revise the application section to include a more detailed description of the types of assumptions (e.g., no outcome effect of discontinuation, or use of external discontinuation rates) that would be needed for a hypothetical strategy, while reiterating that full estimation typically requires IPD. revision: yes

  2. Referee: [Abstract and application section] The abstract and application section describe exploration of treatment-policy versus hypothetical strategies but report no quantitative results, confidence intervals, or sensitivity analyses showing how the pooled estimates or heterogeneity metrics actually change under each strategy. Without these, it is not possible to evaluate whether the estimand choice materially affects conclusions or merely restates the same data under different labels.

    Authors: The application is intended to demonstrate how the framework isolates the intercurrent-event strategy conceptually rather than to deliver a new quantitative re-analysis of the NMA. Because the source trials and existing NMA report treatment-policy results, shifting to hypothetical strategies would require either IPD or additional assumptions beyond the scope of the current illustrative example. We will revise the abstract and application section to clarify this intent and to note that, in practice, sensitivity analyses could be conducted when IPD are available. We will also add a brief discussion of expected directional impacts based on known discontinuation patterns in type 2 diabetes trials, without claiming new numerical estimates. revision: partial

Circularity Check

0 steps flagged

No circularity: pragmatic proposal drawing on established estimand concepts

full rationale

The paper proposes a framework for incorporating estimands into meta-analyses of clinical trials, emphasizing explicit handling of intercurrent event strategies to identify heterogeneity sources. No mathematical derivation chain, equations, or first-principles results are presented that reduce outputs to inputs by construction. The central claim relies on established prior literature (e.g., ICH E9(R1) estimand framework) rather than self-citations that bear the load or fitted parameters renamed as predictions. The semaglutide-dulaglutide NMA application is presented as an illustrative example independent of the proposal itself. This is a conceptual and pragmatic contribution, self-contained against external benchmarks with no evidence of self-definitional, fitted-input, or ansatz-smuggling patterns.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The proposal rests on standard assumptions from the estimand framework and meta-analysis methods. No free parameters are introduced in the abstract description. No new entities are postulated.

axioms (1)
  • domain assumption Standard meta-analysis assumptions hold, including that trial-level data can be aligned to common estimand definitions.
    Invoked when applying the framework to pooled estimates without subject-level data.

pith-pipeline@v0.9.0 · 5872 in / 1341 out tokens · 33792 ms · 2026-05-18T05:53:31.891946+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

118 extracted references · 118 canonical work pages · 1 internal anchor

  1. [1]

    bmj2024; 384

    KahanBC,HindleyJ,EdwardsM,CroS,MorrisTP.Theestimandsframework:aprimerontheICHE9(R1)addendum. bmj2024; 384

    work page

  2. [2]

    https://www.ich.org/page/ich-guideline-implementation; 2025

    ICH Guideline Implementation. https://www.ich.org/page/ich-guideline-implementation; 2025. Accessed: 11-09-2025

    work page 2025

  3. [3]

    JAMA2023; 330(21): 2106–2114

    KahanBC,HallSS,BellerEM,etal.Reportingoffactorialrandomizedtrials:extensionoftheCONSORT2010Statement. JAMA2023; 330(21): 2106–2114

    work page

  4. [4]

    Consensus Statement for Protocols of Factorial Randomized Trials: Extension of the SPIRIT 2013 Statement.JAMA network open2023; 6(12): e2346121

    Kahan BC, Hall SS, Beller EM, et al. Consensus Statement for Protocols of Factorial Randomized Trials: Extension of the SPIRIT 2013 Statement.JAMA network open2023; 6(12): e2346121

    work page 2013

  5. [5]

    Early phase clinical trials extension to guidelines for the content of statistical analysis plans.bmj2022; 376

    Homer V, Yap C, Bond S, et al. Early phase clinical trials extension to guidelines for the content of statistical analysis plans.bmj2022; 376

    work page

  6. [6]

    Defining estimands for efficacy assessment in single arm phase 1b or phase 2 clinical trials in oncology early development.Pharmaceutical Statistics2023; 22(5): 921–937

    Englert S, Mercier F, Pilling EA, et al. Defining estimands for efficacy assessment in single arm phase 1b or phase 2 clinical trials in oncology early development.Pharmaceutical Statistics2023; 22(5): 921–937

    work page

  7. [7]

    LynggaardH,McKendrickS,BairdM,etal.Applyingtheestimandframeworktoclinicalpharmacologytrialswithacase study in bioequivalence.British Journal of Clinical Pharmacology2025; 91(2): 310–324

    work page

  8. [8]

    Review of Recent Pharmacoepidemiologic Post-Market Safety Studies Through the Lens of the Estimand Framework.Therapeutic innovation & regulatory science2025: 1–10

    Ma Y, Haddad J, Liu W, Snyder E, Bennett D, Mayo S. Review of Recent Pharmacoepidemiologic Post-Market Safety Studies Through the Lens of the Estimand Framework.Therapeutic innovation & regulatory science2025: 1–10

    work page

  9. [9]

    Estimands in observational studies: some considerations beyond ICH E9 (R1)

    Li H, Wang C, Chen WC, et al. Estimands in observational studies: some considerations beyond ICH E9 (R1). Pharmaceutical Statistics2022; 21(5): 835–844. 22 REMIRO-AZÓCARET AL

    work page

  10. [10]

    LuijkenK,EekelenvR,GardarsdottirH,GroenwoldRH,GelovenvN.Tellmewhatyouwant,whatyoureallyreallywant: estimandsinobservationalpharmacoepidemiologiccomparativeeffectivenessandsafetystudies.Pharmacoepidemiology and Drug Safety2023; 32(8): 863–872

    work page

  11. [11]

    AdesA,WeltonNJ,DiasS,PhillippoDM,CaldwellDM.Twentyyearsofnetworkmeta-analysis:Continuingcontroversies and recent developments.Research synthesis methods2024; 15(5): 702–727

    work page

  12. [12]

    Broad versus narrow research questions in evidence synthesis: a parallel to (and plea for) estimands.Research Synthesis Methods2024; 15(5): 735–740

    Remiro-Azócar A, Gorst-Rasmussen A. Broad versus narrow research questions in evidence synthesis: a parallel to (and plea for) estimands.Research Synthesis Methods2024; 15(5): 735–740

    work page

  13. [13]

    Toward credible patient-centered meta-analysis.Epidemiology2020; 31(3): 345–352

    Manski CF. Toward credible patient-centered meta-analysis.Epidemiology2020; 31(3): 345–352

    work page

  14. [14]

    Causal inference for meta-analysis and multi-level data structures, with application to randomized studies of Vioxx.Psychometrika2017; 82(2): 459–474

    Sobel M, Madigan D, Wang W. Causal inference for meta-analysis and multi-level data structures, with application to randomized studies of Vioxx.Psychometrika2017; 82(2): 459–474

    work page

  15. [15]

    Toward causally interpretable meta-analysis: transporting inferences from multiple randomized trials to a new target population.Epidemiology2020; 31(3): 334–344

    Dahabreh IJ, Petito LC, Robertson SE, Hernán MA, Steingrimsson JA. Toward causally interpretable meta-analysis: transporting inferences from multiple randomized trials to a new target population.Epidemiology2020; 31(3): 334–344

    work page

  16. [16]

    Causally interpretable meta-analysis: Clearly defined causal effects and two case studies.Research Synthesis Methods2024; 15(1): 61–72

    Rott KW, Bronfort G, Chu H, et al. Causally interpretable meta-analysis: Clearly defined causal effects and two case studies.Research Synthesis Methods2024; 15(1): 61–72

    work page

  17. [17]

    A review of generalizability and transportability.Annual Review of Statistics and Its Application2023; 10: 501–524

    Degtiar I, Rose S. A review of generalizability and transportability.Annual Review of Statistics and Its Application2023; 10: 501–524

    work page

  18. [18]

    External validity.Annual review of political science2021; 24(1): 365–393

    Findley MG, Kikuta K, Denly M. External validity.Annual review of political science2021; 24(1): 365–393

    work page

  19. [19]

    EgamiN,HartmanE.Elementsofexternalvalidity:Framework,design,andanalysis.American Political Science Review 2023; 117(3): 1070–1088

    work page 2023

  20. [20]

    Dahabreh IJ, Robertson SE, Petito LC, Hernán MA, Steingrimsson JA. Efficient and robust methods for causally inter- pretable meta-analysis: Transporting inferences from multiple randomized trials to a target population.Biometrics2023; 79(2): 1057–1072

    work page

  21. [21]

    https: //health.ec.europa.eu/latest-updates/methodological-guideline-quantitative-evidence-synthesis-direct-and-indirect- comparisons-2024-03-25_en; 2024

    Methodological Guideline for Quantitative Evidence Synthesis: Direct and Indirect Comparisons. https: //health.ec.europa.eu/latest-updates/methodological-guideline-quantitative-evidence-synthesis-direct-and-indirect- comparisons-2024-03-25_en; 2024. Accessed: 11-07-2025

    work page 2024

  22. [22]

    Lingvay I, Bauer R, Baker-Knight J, Lawson J, Pratley R. An indirect treatment comparison of semaglutide 2.0 mg vs dulaglutide 3.0 mg and 4.5 mg using multilevel network meta-regression.The Journal of Clinical Endocrinology & Metabolism2022; 107(5): 1461–1469

    work page

  23. [23]

    Consolidated 3-year rolling work plan for the Methodology Working Party

    European Medicines Agency. Consolidated 3-year rolling work plan for the Methodology Working Party. https://www.ema.europa.eu/en/documents/other/consolidated-3-year-rolling-work-plan-methodology-working-party- 2025-2027_en.pdf; 2025. Accessed: 13-09-2025

    work page 2025

  24. [24]

    LynggaardH,KeeneON,MützeT,RehalS.ApplyingtheEstimandFrameworktoNon-InferiorityTrials.Pharmaceutical Statistics2024; 23(6): 1156–1165

    work page

  25. [25]

    Non-Inferiority Clinical Trials to Establish Effectiveness

    Food and Drug Administration (FDA). Non-Inferiority Clinical Trials to Establish Effectiveness. https://www.fda.gov/ media/78504/download; 2016. Accessed: 13-09-2025

    work page 2016

  26. [26]

    ICH E9 (R1) addendum on estimands and sensitivity analysis in clinical trials to the guideline on statistical principles for clinical trials

    European Medicines Agency. ICH E9 (R1) addendum on estimands and sensitivity analysis in clinical trials to the guideline on statistical principles for clinical trials. https://www.ema.europa.eu/en/documents/scientific-guideline/ich- e9-r1-addendum-estimands-sensitivity-analysis-clinical-trials-guideline-statistical-principles_en.pdf; 2020. Accessed: 17-07-2025

    work page 2020

  27. [27]

    REMIRO-AZÓCARET AL 23

    KeeneON,LynggaardH,EnglertS,LaniusV,WrightD.Whyestimandsareneededtodefinetreatmenteffectsinclinical trials.BMC medicine2023; 21(1): 276. REMIRO-AZÓCARET AL 23

    work page

  28. [28]

    Estimands: bringing clarity and focus to research questions in clinical trials.BMJ open2022; 12(1): e052953

    Clark TP, Kahan BC, Phillips A, White I, Carpenter JR. Estimands: bringing clarity and focus to research questions in clinical trials.BMJ open2022; 12(1): e052953

    work page

  29. [29]

    MitroiuM,TeerenstraS,OudeRengerinkK,PétavyF,RoesKC.Estimationoftreatmenteffectsinshort-termdepression studies.AnevaluationbasedontheICHE9(R1)estimandsframework.Pharmaceutical Statistics2022;21(5):1037–1057

    work page

  30. [30]

    MitroiuM,OudeRengerinkK,TeerenstraS,PétavyF,RoesK.Anarrativereviewofestimandsindrugdevelopmentand regulatory evaluation: old wine in new barrels?.Trials2020; 21(1): 671

    work page

  31. [31]

    Morga A, Latimer NR, Scott M, Hawkins N, Schlichting M, Wang J. Is intention to treat still the gold standard or should health technology assessment agencies embrace a broader Estimands framework?: insights and perspectives from the National Institute for Health and Care Excellence and Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen on th...

    work page

  32. [32]

    Estimands for overall survival in clinical trials with treatment switching in oncology.Pharmaceutical Statistics2022; 21(1): 150–162

    Manitz J, Kan-Dobrosky N, Buchner H, et al. Estimands for overall survival in clinical trials with treatment switching in oncology.Pharmaceutical Statistics2022; 21(1): 150–162

    work page

  33. [33]

    Latimer NR, Abrams KR, Lambert PC, et al. Adjusting survival time estimates to account for treatment switching in randomized controlled trials—an economic evaluation context: methods, limitations, and recommendations.Medical Decision Making2014; 34(3): 387–402

    work page

  34. [34]

    JacksonD,RanD,ZhangF,etal.NewMethodsforTwo-StageTreatmentSwitchingEstimation.Pharmaceutical Statistics 2025; 24(1): e2462

    work page 2025

  35. [35]

    KeeneON,RubergS,SchachtA,etal.Whatmattersmost?Differentstakeholderperspectivesonestimandsforaninvented case study in COPD.Pharmaceutical Statistics2020; 19(4): 370–387

    work page

  36. [36]

    Defining clinical trial estimands: a practical guide forstudyteamswithexamplesbasedonapsychiatricdisorder.Therapeutic Innovation & Regulatory Science2023;57(5): 911–939

    Polverejan E, O’Kelly M, Hefting N, Norton JD, Lim P, Walton MK. Defining clinical trial estimands: a practical guide forstudyteamswithexamplesbasedonapsychiatricdisorder.Therapeutic Innovation & Regulatory Science2023;57(5): 911–939

    work page

  37. [37]

    Estimation methods for estimands using the treatment policy strategy; a simulation study based on the PIONEER 1 Trial.Pharmaceutical Statistics2025; 24(2): e2472

    Bell J, Drury T, Mütze T, et al. Estimation methods for estimands using the treatment policy strategy; a simulation study based on the PIONEER 1 Trial.Pharmaceutical Statistics2025; 24(2): e2472

    work page

  38. [38]

    RoB 2: a revised tool for assessing risk of bias in randomised trials.bmj2019; 366

    Sterne JA, Savović J, Page MJ, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials.bmj2019; 366

    work page

  39. [39]

    https://health.ec.europa.eu/publications/ guidance-validity-clinical-studies-joint-clinical-assessments_en; 2024

    Guidance on the validity of clinical studies for joint clinical assessments. https://health.ec.europa.eu/publications/ guidance-validity-clinical-studies-joint-clinical-assessments_en; 2024. Accessed: 31-07-2025

    work page 2024

  40. [40]

    Poythress J, Morga A. HTA50 Assessing the Risk of Bias in Clinical Trials for Health Technology Assessments: Should ExistingToolsReflecttheICHE9(R1)AddendumonEstimandsandSensitivityAnalyses?.Value in Health2023;26(12): S329

    work page

  41. [41]

    The well-built clinical question: a key to evidence-based decisions..ACP journal club1995; 123(3): A12–3

    Richardson WS, Wilson MC, Nishikawa J, Hayward RS. The well-built clinical question: a key to evidence-based decisions..ACP journal club1995; 123(3): A12–3

    work page

  42. [42]

    https://health.ec.europa.eu/publications/guidance-outcomes-joint- clinical-assessments_en; 2024

    Guidance on outcomes for joint clinical assessments. https://health.ec.europa.eu/publications/guidance-outcomes-joint- clinical-assessments_en; 2024. Accessed: 16-07-2025

    work page 2024

  43. [43]

    FrandsenTF,NielsenMFB,LindhardtCL,EriksenMB.UsingthefullPICOmodelasasearchtoolforsystematicreviews resulted in lower recall for some PICO elements.Journal of clinical epidemiology2020; 127: 69–75

    work page

  44. [44]

    Preferredreporting itemsfor systematicreviews andmeta- analyses: the PRISMA statement.International journal of surgery2010; 8(5): 336–341

    Moher D,Liberati A,Tetzlaff J,Altman DG,Group P,others . Preferredreporting itemsfor systematicreviews andmeta- analyses: the PRISMA statement.International journal of surgery2010; 8(5): 336–341

    work page

  45. [45]

    The PRISMA statement extension for systematic reviews incorporating network meta-analysis: PRISMA-NMA.Medicina Clínica (English Edition)2016; 147(6): 262–266

    Hutton B, Catala-Lopez F, Moher D. The PRISMA statement extension for systematic reviews incorporating network meta-analysis: PRISMA-NMA.Medicina Clínica (English Edition)2016; 147(6): 262–266. 24 REMIRO-AZÓCARET AL

    work page 2016

  46. [46]

    The current landscape of HTA framework and key challenges.In press, Statistics in Biopharmaceutical Research2025

    Jen MH, Mt-Isa S, Chu H, et al. The current landscape of HTA framework and key challenges.In press, Statistics in Biopharmaceutical Research2025

    work page

  47. [47]

    The impact of additive population (s), intervention, comparator (s), and outcomes in a European joint clinical health technology assessment.Value in Health2024; 27(12): 1722–1731

    Engen vA, Krüger R, Parnaby A, et al. The impact of additive population (s), intervention, comparator (s), and outcomes in a European joint clinical health technology assessment.Value in Health2024; 27(12): 1722–1731

    work page

  48. [48]

    Accessed: 09-07-2025

    Guidanceonthescopingprocess.https://health.ec.europa.eu/publications/guidance-scoping-process_en;2024. Accessed: 09-07-2025

    work page 2024

  49. [49]

    Parametric G-computation for Compatible Indirect Treatment Comparisons with Limited Individual Patient Data.Research synthesis methods2022; 13(6): 716–744

    Remiro-Azócar A, Heath A, Baio G. Parametric G-computation for Compatible Indirect Treatment Comparisons with Limited Individual Patient Data.Research synthesis methods2022; 13(6): 716–744

    work page

  50. [50]

    National Institute for Health and Care Excellence technology appraisal guidance: Cabozantinib for previ- ously treated advanced differentiated thyroid cancer unsuitable for or refractory to radioactive iodine. https: //www.nice.org.uk/guidance/ta928/resources/cabozantinib-for-previously-treated-advanced-differentiated-thyroid- cancer-unsuitable-for-or-ref...

    work page 2023

  51. [51]

    BroseMS,RobinsonB,ShermanSI,etal.Cabozantinibforradioiodine-refractorydifferentiatedthyroidcancer(COSMIC- 311): a randomised, double-blind, placebo-controlled, phase 3 trial.The Lancet Oncology2021; 22(8): 1126–1138

    work page

  52. [52]

    Accessed: 17-07-2025

    National Institute for Health and Care Excellence final scope: Cabozantinib for previously treated advanced differentiated thyroidcancerunsuitablefororrefractorytoradioactiveiodine.https://www.nice.org.uk/guidance/ta928/documents/final- scope; 2022. Accessed: 17-07-2025

    work page 2022

  53. [53]

    https://www.ema.europa.eu/en/documents/variation- report/cabometyx-h-c-004163-ii-0023-epar-assessment-report-variation_en.pdf; 2022

    European Medicines Agency assessment report for Cabometyx. https://www.ema.europa.eu/en/documents/variation- report/cabometyx-h-c-004163-ii-0023-epar-assessment-report-variation_en.pdf; 2022. Accessed: 17-07-2025

    work page 2022

  54. [54]

    Remiro-AzócarA.Someconsiderationsontargetestimandsforhealthtechnologyassessment.Statistics in Medicine2022; 41(28): 5592–5596

    work page

  55. [55]

    Methods Guide for Health Technology Assessment

    Canada’s Drug Agency. Methods Guide for Health Technology Assessment. https://www.cda-amc.ca/sites/default/files/ MG%20Methods/MG0030-Quantitative-Methods-Manual-Line-Numbered.pdf; 2024. Accessed: 17-08-2025

    work page 2024

  56. [56]

    PhillippoDM,AdesAE,DiasS,PalmerS,AbramsKR,WeltonNJ.Methodsforpopulation-adjustedindirectcomparisons in health technology appraisal.Medical Decision Making2018; 38(2): 200–211

    work page

  57. [57]

    Estimands and Their Implications for Evidence Synthesis for Oncology: A Simulation Study of Treatment Switching in Meta-Analysis.arXiv preprint arXiv:2411.143232024

    Vuong Q, Metcalfe RK, Remiro-Azócar A, Gorst-Rasmussen A, Keene O, Park JJ. Estimands and Their Implications for Evidence Synthesis for Oncology: A Simulation Study of Treatment Switching in Meta-Analysis.arXiv preprint arXiv:2411.143232024

    work page arXiv

  58. [58]

    MützeT,BellJ,EnglertS,etal.Principlesfordefiningestimandsinclinicaltrials—Aproposal.Pharmaceutical Statistics 2025; 24(1): e2432

    work page 2025

  59. [59]

    FletcherC,HeftingN,WrightM,etal.Marking2-yearsofnewthinkinginclinicaltrials:theestimandjourney.Therapeutic Innovation & Regulatory Science2022; 56(4): 637–650

    work page

  60. [60]

    Estimand Framework and Statistical Considerations for Integrated Analysis of Clinical Trial Safety Data.Therapeutic Innovation & Regulatory Science2024; 58(6): 1120–1128

    Hedman K, Kordzakhia G, Li H, Nyström P. Estimand Framework and Statistical Considerations for Integrated Analysis of Clinical Trial Safety Data.Therapeutic Innovation & Regulatory Science2024; 58(6): 1120–1128

    work page

  61. [61]

    Diabetes care2020; 43(2): 487–493

    BuseJB,WexlerDJ,TsapasA,etal.2019updateto:managementofhyperglycemiaintype2diabetes,2018.Aconsensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes care2020; 43(2): 487–493

    work page 2018

  62. [62]

    Efficacy and safety of GLP-1 receptor agonists across the spectrum of type 2 diabetes mellitus

    Leiter LA, Nauck MA. Efficacy and safety of GLP-1 receptor agonists across the spectrum of type 2 diabetes mellitus. Experimental and Clinical Endocrinology & Diabetes2017; 125(07): 419–435

    work page

  63. [63]

    Pratley RE, Aroda VR, Lingvay I, et al. Semaglutide versus dulaglutide once weekly in patients with type 2 diabetes (SUSTAIN 7): a randomised, open-label, phase 3b trial.The lancet Diabetes & endocrinology2018; 6(4): 275–286. REMIRO-AZÓCARET AL 25

    work page

  64. [64]

    Defining and characterizing the progression of type 2 diabetes.Diabetes care2009; 32(Suppl 2): S151

    Fonseca VA. Defining and characterizing the progression of type 2 diabetes.Diabetes care2009; 32(Suppl 2): S151

    work page

  65. [65]

    FríasJP,AuerbachP,BajajHS,etal.Efficacyandsafetyofonce-weeklysemaglutide2·0mgversus1·0mginpatientswith type 2 diabetes (SUSTAIN FORTE): a double-blind, randomised, phase 3B trial.The Lancet Diabetes & Endocrinology 2021; 9(9): 563–574

    work page 2021

  66. [66]

    FriasJP, BonoraE,Nevarez RuizL,et al.Efficacyand safetyofdulaglutide 3.0mgand 4.5mgversus dulaglutide1.5mg in metformin-treated patients with type 2 diabetes in a randomized controlled trial (AWARD-11).Diabetes Care2021; 44(3): 765–773

    work page

  67. [67]

    Risk of bias in network meta-analysis (RoB NMA) tool.bmj2025; 388

    Lunny C, Higgins JP, White IR, et al. Risk of bias in network meta-analysis (RoB NMA) tool.bmj2025; 388

    work page

  68. [68]

    https://cdn.clinicaltrials.gov/large-docs/04/NCT02648204/Prot_000.pdf; 2015

    Protocol:Efficacyandsafetyofsemaglutideversusdulaglutideasanadd-ontometformininsubjectswithtype2diabetes. https://cdn.clinicaltrials.gov/large-docs/04/NCT02648204/Prot_000.pdf; 2015. Accessed: 22-07-2025

    work page 2015

  69. [69]

    https://cdn.clinicaltrials.gov/large-docs/04/NCT02648204/SAP_001.pdf; 2017

    Statistical analysis plan: Efficacy and safety of semaglutide versus dulaglutide as an add-on to metformin in subjects with type 2 diabetes. https://cdn.clinicaltrials.gov/large-docs/04/NCT02648204/SAP_001.pdf; 2017. Accessed: 22-07-2025

    work page 2017

  70. [70]

    https://cdn.clinicaltrials.gov/large-docs/32/NCT03989232/Prot_000.pdf; 2020

    Protocol:Efficacyandsafetyofsemaglutide2.0mgs.c.once-weeklycomparedtosemaglutide1.0mgs.c.once-weeklyin subjects with type 2 diabetes. https://cdn.clinicaltrials.gov/large-docs/32/NCT03989232/Prot_000.pdf; 2020. Accessed: 22-07-2025

    work page 2020

  71. [71]

    once-weekly compared to semaglutide 1.0 mg s.c

    Statistical analysis plan: Efficacy and safety of semaglutide 2.0 mg s.c. once-weekly compared to semaglutide 1.0 mg s.c. once-weekly in subjects with type 2 diabetes. https://cdn.clinicaltrials.gov/large-docs/32/NCT03989232/SAP_002.pdf

    work page

  72. [72]

    Accessed: 22-07-2025

    work page 2025

  73. [73]

    https://cdn.clinicaltrials.gov/large-docs/02/ NCT03495102/Prot_000.pdf; 2018

    Protocol: A Randomized, Double-Blind, Parallel Arm Study of the Efficacy and Safety of Investigational Dulaglutide Doses When Added to Metformin in Patients with Type 2 Diabetes Mellitus. https://cdn.clinicaltrials.gov/large-docs/02/ NCT03495102/Prot_000.pdf; 2018. Accessed: 22-07-2025

    work page 2018

  74. [74]

    Accessed: 22-07-2025

    A Randomized, Double-Blind, Parallel Arm Study of the Efficacy and Safety of Investigational Dulaglutide Doses When AddedtoMetformininPatientswithType2DiabetesMellitus.https://cdn.clinicaltrials.gov/large-docs/02/NCT03495102/ SAP_001.pdf; 2019. Accessed: 22-07-2025

    work page 2019

  75. [75]

    DaviesMJ,D’AlessioDA,FradkinJ,etal.Managementofhyperglycaemiaintype2diabetes,2018.Aconsensusreportby theAmericanDiabetesAssociation(ADA)andtheEuropeanAssociationfortheStudyofDiabetes(EASD).Diabetologia 2018; 61(12): 2461–2498

    work page 2018

  76. [76]

    LaniusV,GlockerB,LöschC,etal.Realizingthebenefitsoftheestimandframeworkwhenreportingandcommunicating clinical trial results—some recommendations.Trials2025; 26(1): 1–16

    work page

  77. [77]

    A basic introduction to fixed-effect and random-effects models for meta-analysis.Research synthesis methods2010; 1(2): 97–111

    Borenstein M, Hedges LV, Higgins JP, Rothstein HR. A basic introduction to fixed-effect and random-effects models for meta-analysis.Research synthesis methods2010; 1(2): 97–111

    work page

  78. [78]

    RückerG.Networkmeta-analysis,electricalnetworksandgraphtheory.Research synthesis methods2012;3(4):312–324

    work page

  79. [79]

    netmeta: an R package for network meta-analysis using frequentist methods.Journal of Statistical Software2023; 106: 1–40

    Balduzzi S, Rücker G, Nikolakopoulou A, et al. netmeta: an R package for network meta-analysis using frequentist methods.Journal of Statistical Software2023; 106: 1–40

    work page

  80. [80]

    John Wiley & Sons

    Higgins JP, Thomas J, Chandler J, et al.Cochrane handbook for systematic reviews of interventions. John Wiley & Sons . 2019

    work page 2019

Showing first 80 references.