Distribution of postpartum blood loss: modeling, estimation and application to clinical trials

José Ferreira De Carvalho,Gilda Piaggio,A Metin Gülmezoglu,Mariana Widmer,Daniel Wojdyla

doi:10.1186/s12978-018-0641-1

Abstract

BackgroundThe loss of large amounts of blood postpartum can lead to severe maternal morbidity and mortality. Understanding the nature of postpartum blood loss distribution is critical for the development of efficient analysis techniques when comparing treatments to prevent this event. When blood loss is measured, resulting in a continuous volume measure, often this variable is categorized in classes, and reduced to an indicator of volume greater than a cutoff point. This reduction of volume to classes entails a substantial loss of information. As a consequence, very large trials are needed to assess clinically important differences between treatments to prevent postpartum haemorrhage.MethodsThe authors explore the nature of postpartum blood loss distribution, assuming that the physical properties of blood loss lead to a lognormal distribution. Data from four clinical trials and one observational study are used to confirm this empirically. Estimates of probabilities of postpartum haemorrhage events ‘blood loss greater than a cutoff point’ and relative risks are obtained from the fitted lognormal distributions. Confidence intervals for relative risk are obtained by bootstrap techniques.ResultsA variant of the lognormal distribution, the three-parameter lognormal distribution, showed an excellent fit to postpartum blood loss data of the four trials and the observational study. A measurement quality assessment showed that problems of digit preference and lower limit of detection were well handled by the lognormal fit. The analysis of postpartum haemorrhage events based on a lognormal distribution improved the efficiency of the estimates. Sample size calculation for a hypothetical future trial showed that the application of this procedure permits a reduction of sample size for treatment comparison.ConclusionA variant of the lognormal distribution fitted very well postpartum blood loss data from different geographical areas, suggesting that the lognormal distribution might fit postpartum blood loss universally. An approach of analysis of postpartum haemorrhage events based on the lognormal distribution improves efficiency of estimates of probabilities and relative risk, and permits a reduction of sample size for treatment comparison.Trial registrationThis paper reports secondary analyses for trials registered at Australian New Zealand Clinical Trials Registry (ACTRN 12608000434392 and ACTRN12614000870651); and at clinicaltrials.gov (NCT00781066).

Highlights

The loss of large amounts of blood postpartum can lead to severe maternal morbidity and mortality
The aim of this paper is to show empirically that the distribution of postpartum blood loss volume is lognormal, that the lognormal distribution can be used as a model for a lognormal analysis of postpartum blood loss, and to present the following applications of this finding for clinical trials: 1) Analyses using continuous blood loss volume based on the lognormal distribution improve the efficiency of comparisons of the proportions of severe PPH (sPPH) and postpartum haemorrhage (PPH) between treatment groups
A possible limitation of the approach we propose is whether the lognormal distribution is appropriate for modeling postpartum blood loss when there is a strong interest in the estimation of tail probabilities of the order of magnitude of 1 to 4%

Summary

Introduction

The loss of large amounts of blood postpartum can lead to severe maternal morbidity and mortality. When blood loss is measured, resulting in a continuous volume measure, often this variable is categorized in classes, and reduced to an indicator of volume greater than a cutoff point. This reduction of volume to classes entails a substantial loss of information. It is accepted that clinical trials conducted to compare treatments to prevent post partum haemorrhage should measure blood loss weight or volume, as opposed to subjective evaluation. In trials to compare treatments to prevent postpartum haemorrhage, the use of an indicator variable, added to the low prevalence, results in very large sample sizes needed to detect improvements in prevention of blood loss endpoints when new treatments or procedures are evaluated

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