A treatment strategy with nifedipine versus labetalol for women with pregnancy hypertension: study protocol for a randomised controlled trial (Giant PANDA)

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Abstract

Background

Approximately one in ten women have high blood pressure during pregnancy. Hypertension is associated with adverse maternal and perinatal outcomes, and as treatment improves maternal outcomes, antihypertensive treatment is recommended. Previous trials have been unable to provide a definitive answer on which antihypertensive treatment is associated with optimal maternal and neonatal outcomes and the need for robust evidence evaluating maternal and infant benefits and risks remains an important, unanswered question for research and clinical communities.

Methods

The Giant PANDA study is a pragmatic, open-label, multicentre, randomised controlled trial of a treatment initiation strategy with nifedipine (calcium channel blocker), versus labetalol (mixed alpha/beta blocker) in 2300 women with pregnancy hypertension. The primary objective is to evaluate if treatment with nifedipine compared to labetalol in women with pregnancy hypertension reduces severe maternal hypertension without increasing fetal or neonatal death or neonatal unit admission. Subgroup analyses will be undertaken by hypertension type (chronic, gestational, pre-eclampsia), diabetes (yes, no), singleton (yes, no), self-reported ethnicity (Black, all other), and gestational age at randomisation categories (11 + 0 to 19 + 6, 20 + 0 to 27 + 6, 28 + 0 to 34 + 6 weeks). A cost-effectiveness analysis using an NHS perspective will be undertaken using a cost-consequence analysis up to postnatal hospital discharge and an extrapolation exercise with a lifetime horizon conditional on the results of the cost-consequence analysis.

Discussion

This trial aims to address the uncertainty of which antihypertensive treatment is associated with optimal maternal and neonatal outcomes. The trial results are intended to provide definitive evidence to inform guidelines and linked, shared decision-making tools, thus influencing clinical practice.

Trial registration

EudraCT number: 2020–003410-12, ISRCTN: 12,792,616 registered on 18 November 2020.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-023-07582-9.

Related collections

Most cited references 19

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Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L)

M. Herdman, C. Gudex, S Lloyd … (2011)

Purpose This article introduces the new 5-level EQ-5D (EQ-5D-5L) health status measure. Methods EQ-5D currently measures health using three levels of severity in five dimensions. A EuroQol Group task force was established to find ways of improving the instrument’s sensitivity and reducing ceiling effects by increasing the number of severity levels. The study was performed in the United Kingdom and Spain. Severity labels for 5 levels in each dimension were identified using response scaling. Focus groups were used to investigate the face and content validity of the new versions, including hypothetical health states generated from those versions. Results Selecting labels at approximately the 25th, 50th, and 75th centiles produced two alternative 5-level versions. Focus group work showed a slight preference for the wording ‘slight-moderate-severe’ problems, with anchors of ‘no problems’ and ‘unable to do’ in the EQ-5D functional dimensions. Similar wording was used in the Pain/Discomfort and Anxiety/Depression dimensions. Hypothetical health states were well understood though participants stressed the need for the internal coherence of health states. Conclusions A 5-level version of the EQ-5D has been developed by the EuroQol Group. Further testing is required to determine whether the new version improves sensitivity and reduces ceiling effects.

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The beliefs about medicines questionnaire: The development and evaluation of a new method for assessing the cognitive representation of medication

Robert Horne, John A Weinman, Maittew Hankins (1999)

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Model parameter estimation and uncertainty analysis: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group-6.

Andrew H Briggs, Milton C. Weinstein, Elisabeth Fenwick … (2012)

A model's purpose is to inform medical decisions and health care resource allocation. Modelers employ quantitative methods to structure the clinical, epidemiological, and economic evidence base and gain qualitative insight to assist decision makers in making better decisions. From a policy perspective, the value of a model-based analysis lies not simply in its ability to generate a precise point estimate for a specific outcome but also in the systematic examination and responsible reporting of uncertainty surrounding this outcome and the ultimate decision being addressed. Different concepts relating to uncertainty in decision modeling are explored. Stochastic (first-order) uncertainty is distinguished from both parameter (second-order) uncertainty and from heterogeneity, with structural uncertainty relating to the model itself forming another level of uncertainty to consider. The article argues that the estimation of point estimates and uncertainty in parameters is part of a single process and explores the link between parameter uncertainty through to decision uncertainty and the relationship to value-of-information analysis. The article also makes extensive recommendations around the reporting of uncertainty, both in terms of deterministic sensitivity analysis techniques and probabilistic methods. Expected value of perfect information is argued to be the most appropriate presentational technique, alongside cost-effectiveness acceptability curves, for representing decision uncertainty from probabilistic analysis.

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Author and article information

Contributors

Lucy C. Chappell:

ORCID: http://orcid.org/0000-0001-6219-3379

lucy.chappell@kcl.ac.uk

Journal

Journal ID (nlm-ta): Trials

Journal ID (iso-abbrev): Trials

Title: Trials

Publisher: BioMed Central (London )

ISSN (Electronic): 1745-6215

Publication date (Electronic): 12 September 2023

Publication date PMC-release: 12 September 2023

Publication date Collection: 2023

Volume: 24

Electronic Location Identifier: 584

Affiliations

[1 ]GRID grid.13097.3c, ISNI 0000 0001 2322 6764, Department of Women and Children’s Health, School of Life Course Sciences, , King’s College London, ; London, UK

[2 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, Neonatal Medicine, School of Public Health, Faculty of Medicine, , Imperial College London, ; London, UK

[3 ]GRID grid.7372.1, ISNI 0000 0000 8809 1613, Warwick Clinical Trials Unit, Warwick Medical School, , University of Warwick, ; Coventry, UK

[4 ]Action On Pre-Eclampsia, Evesham, UK

[5 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, National Perinatal Epidemiology Unit Clinical Trials Unit, Nuffield Department of Population Health, , University of Oxford, ; Oxford, UK

[6 ]GRID grid.6572.6, ISNI 0000 0004 1936 7486, Birmingham Clinical Trials Unit, , Institute of Applied Health Research, University of Birmingham, ; Birmingham, UK

[7 ]GRID grid.13097.3c, ISNI 0000 0001 2322 6764, Institute of Women and Children’s Health, , King’s College London, ; London, UK

[8 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Nuffield Department of Primary Care Health Sciences, , University of Oxford, ; Oxford, UK

[9 ]GRID grid.451052.7, ISNI 0000 0004 0581 2008, Obstetric Medicine, Guy’s and St Thomas’ Hospitals NHS Trust, ; London, UK

[10 ]GRID grid.13097.3c, ISNI 0000 0001 2322 6764, Clinical Pharmacology, School of Cardiovascular and Metabolic Medicine & Sciences, , King’s College London British Heart Foundation Centre of Research Excellence, ; London, UK

[11 ]GRID grid.5379.8, ISNI 0000000121662407, Faculty of Biology, Medicine and Health, , The University of Manchester, ; Manchester, UK

Author information

Lucy C. Chappell http://orcid.org/0000-0001-6219-3379

Article

Publisher ID: 7582

DOI: 10.1186/s13063-023-07582-9

PMC ID: 10496358

PubMed ID: 37700365

SO-VID: ac6e4b0d-ecad-491e-a114-c8a62356b1af

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 26 June 2023

Date accepted : 11 August 2023

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100000664, Health Technology Assessment Programme;

Award ID: NIHR128721

Award Recipient : Lucy C. Chappell

Custom metadata

ScienceOpen disciplines: Medicine

Keywords: hypertension,pregnancy,randomised controlled trial,antihypertensives,blood pressure

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ScienceOpen disciplines: Medicine

Keywords: hypertension, pregnancy, randomised controlled trial, antihypertensives, blood pressure

A treatment strategy with nifedipine versus labetalol for women with pregnancy hypertension: study protocol for a randomised controlled trial (Giant PANDA)

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Abstract

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Discussion

Trial registration

Supplementary Information

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Most cited references 19

Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L)

The beliefs about medicines questionnaire: The development and evaluation of a new method for assessing the cognitive representation of medication

Model parameter estimation and uncertainty analysis: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group-6.

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