predictors for adverse maternal and fetal outcomes in high risk pregnancy

340 Pages·2017·3.94 MB·English

TITLE PAGE

PREDICTORS FOR ADVERSE MATERNAL AND FETAL OUTCOMES IN HIGH
RISK PREGNANCY

FIONA MU-LING CHEONG-SEE

A thesis submitted to Queen Mary University London
For the degree of

MD (Res)
Doctor of Medicine (Research)

December 2016
STATEMENT OF ORIGINALITY

I, Fiona Mu-ling Cheong-See, confirm that the research included within this thesis is my own
work or that where it has been carried out in collaboration with, or supported by others, that
this is duly acknowledged below and my contribution indicated. Previously published
material is also acknowledged below.

I attest that I have exercised reasonable care to ensure that the work is original, and does not
to the best of my knowledge break any UK law, infringe any third party’s copyright or other
Intellectual Property Right, or contain confidential material.

I accept that the College has the right to use plagiarism detection software to check the
electronic version of the thesis.

I confirm that this thesis has not been previously submitted for the award of a degree by this
or any other university.

The copyright of this thesis rests with the author and no quotation from it or information
derived from it may be published without the prior written consent of the author.

Signature:
Date: 22/12/16
Details of collaboration and publications
DETAILS OF COLLABORATION

Chapter 4.1
Collaboration with Shakila Thangaratinam (supervisor), Robert Walton (supervisor, genetics
input), Manpreet Sahemey (co-reviewer, study selection, data extraction, quality assessment),
Valerie Kuan (co-reviewer, genetics input), Golnessa Hamedi (data extraction and quality
assessment), Rachael Eyitayo (data extraction and quality assessment), Derick Yates (search
strategy input).

Chapter 4.2
Collaboration with Joost Akkermans (co-reviewer, data extraction, quality assessment, data
analysis), Shakila Thangaratinam (supervisor), Javier Zamora (data analysis and statistical
input).
Thanks to EBM-CONNECT (Evidence-Based Medicine COllaboratioN: Network for
systematic reviews and guideline development researCh and dissemination) to facilitating
international collaboration; Peter von Dadelszen (St George’s University, London), Ben W
Mol (University of Adelaide, London), Mark Brown (St George Hospital, Sydney) for
sharing primary study data.

Chapter 4.3
Collaboration with Shakila Thangaratinam (supervisor and development of composite
outcomes), Stephen Kempley (neonatal input and development of composite outcomes),
Divyen Shah (neonatal input and development of composite outcomes), Khalid Khan
(supervisor and development of composite outcomes) Ewelina Rogozinska (statistical input
and development of composite outcomes), John Allotey (dissemination of survey and
interpretation).

Chapter 5.1
Collaboration with Ewoud Schuit (co-reviewer, data extraction, quality assessment, data
anaysis), Shakila Thangaratinam (supervisor), Basky Thilaganathan (supervisor), Javier
Zamora (data analysis and statistical support), David Arroyo-Manzano (data analysis and
statistical support). Thanks to Global Obstetric NETwork (GONet) and Twins Individual
Patient Data group and the following colleagues for sharing primary data and input into the
final draft: Asma Khalil, Jon Barrett, KS Joseph, Elizabeth Asztalos, Liesbeth Lewi, Arianne
Lim, Sophie Liem, Jane Norman, John Morrison, Andrew Combs, Thomas Garite, Kimberly
Maurel, Vicente Serra, Alfredo Perales, Line Rode, Katharina Worda, Anwar Nassar, Mona
Aboulghar, Dwight Rouse, Elizabeth Thom, Fionnuala Breathnach, Soichiro Nakayama,
Francesca Russo, Julian Robinson, Jodie Dodd, Roger Newman, Sohinee Bhattacharya,
Selphee Tang, Stephen Wood, Ben Mol.
Chapter 6.1
Collaboration with Emily Kleinrouweler (co-reviewer, study selection, data extraction,
quality assessment), Ewoud Schuit (co-reviewer, study selection, data extraction, quality
assessment), Ben Mol (supervisor), Shakila Thangaratinam (supervisor), Khalid Khan
(supervisor), Gary Collins (statistical input), Eva Pajkrt (statistical input), Anneke Kwee
(statistical input), Karl Moons (statistical input)
Chapter 6.2
Collaboration with John Allotey (co-reviewer, PREP study co-ordinator), Shakila
Thangaratinam (supervisor, PREP Principal Investigator), Khalid Khan (supervisor, PREP
Chief Investigator), Nadine Marlin (statistical input), Ewoud Schuit (statistical input), Gerben
ter Riet (statistical input), Ben Mol (statistical input).
My contribution to each chapter is detailed at the end of each chapter.
PUBLICATIONS IN PEER REVIEWED JOURNALS FROM THE THESIS

1. Cheong-See F, Schuit E, Arroyo-Manzano D, Khalil A, Barrett J, Joseph KS,
Asztalos E, Lewi L, Lim A, Liem S, Norman JE, Morrison J, Combs CA, Garite TJ,
Maurel K, Serra V, Perales A, Rode L, Worda K, Nassar A, Aboulghar M, Rouse D,
Thom E, Breathnach F, Nakayama S, Russo FM, Robinson JN, Dodd JM, Newman
RB, Bhattacharya S, Tang S, Mol BWJ, Zamora J, Thilaganathan B, Thangaratinam
S. (2016) Prospective risk of stillbirth and neonatal complications in twin
pregnancies: systematic review and meta-analysis. BMJ 2016; 354:i4353
2. Cheong-See F, Allotey J, Marlin N, Mol BW, Schuit E, Ter Riet G, Riley RD, Moons
K, Khan KS, Thangaratinam S. (2016) Prediction models in obstetrics: understanding
the treatment paradox and potential solutions to the threat it poses. BJOG 2016,doi
10.1111/1471-0528.13859.
3. Kleinrouweler CE, Cheong-See FM, Collins GS, Kwee A, Thangaratinam S, Khan
KS, Mol BW, Pajkrt E, Moons KG, Schuit E. (2016) Prognostic models in obstetrics:
available, but far from applicable. AJOG 2016 214(1):79-90.e36. doi:
10.1016/j.ajog.2015.06.013.
4. Fong F, Rogozinska E, Allotey J, Kempley S, Shah DK, Thangaratinam S. (2014)
Development of Maternal and Neonatal Composite Outcomes for Trials Evaluating
Management of Late-onset Pre-eclampsia. Hypertens Pregnancy. 2014 May; 33(2):
115-31. Doi: 10.3109/10641955.2013.837176.
5. Fong FM, Sahemey MK, Hamedi G, Eyitayo R, Yates D, Kuan V, Thangaratinam S,
Walton R. (2014) Maternal Genotype and Severe Preeclampsia: A HuGE Review.
Am J Epidemiol. Am J of Epidemiol 2014; 180 (4): 335:345.
6. Cheong-See F, Akkermans J, Zamora J, Thangaratinam S. Accuracy of individual
tests to predict complications in women with pre-eclampsia: a systematic review
(submitted and under review by Hypertension in Pregnancy journal)
ABSTRACT
This thesis aims to undertake health technology assessments in high risk pregnancies through
the following objectives:
1. In women with pre-eclampsia,
a) To evaluate the association of maternal genotype and severe pre-eclampsia
b) To assess the accuracy of tests in predicting adverse pregnancy outcomes
c) To develop composite outcomes for reporting in trials on late onset pre-eclampsia
2. In women with multiple pregnancy,
a) To study the association between chorionicity and stillbirth
b) To identify the optimal timing of delivery in monochorionic and dichorionic twin
pregnancies
3. In the field of prediction research in obstetrics
a) To provide an overview of the existing prognostic models and their qualities
b) To evaluate the methodological challenges and potential solutions in developing a
prognostic model for complications in pre-eclampsia
Methods
The following research methodologies were used: Delphi survey, systematic reviews and
meta-analyses.
Results
1. a) Maternal genotype and severe pre-eclampsia:
57 studies evaluated 50 genotypes; increased risk of severe pre-eclampsia with
thromobophilic genes.
b) Accuracy of tests in predicting pre-eclampsia complications:
37 studies evaluated 13 tests. No single test showed high sensitivity and specificity.
c) Delphi survey of 18/20 obstetricians and 18/24 neonatologists identified clinically
important maternal and neonatal outcomes and maternal and neonatal composite
outcomes were developed.
2. Prospective risk of stillbirth and neonatal deaths in uncomplicated monochorionic and
dichorionic twin pregnancies:
32 studies were included. In dichorionic twin pregnancies, the risk of stillbirths was
balanced against neonatal death at 37 weeks’ gestation. In monochorionic
pregnancies, there was a trend towards increase in stillbirths after 36 weeks but this
was not significant.
3. a) From 177 studies included, 263 obstetric prediction models were developed for 40
different outcomes, most commonly pre-eclampsia, preterm delivery, mode of
delivery and small for gestational age neonates.
b) The obstetric prognostic model challenge of dealing with treatment paradox was
explored and seven potential solutions proposed by expert consensus.
Conclusion
I have identified the strength of association for genes associated with complications in pre-
eclampsia, components for composite outcomes for reporting in studies on pre-eclampsia,
and the optimal timing of delivery for twin pregnancies. My work has highlighted the gaps in
prediction research in obstetrics and the limitations of individual tests in pre-eclampsia.
DEDICATION

To Patrick, Jacob, Mum and my family