Re: Impact of analysis technique on our understanding of the
natural history of labour
Jun Zhang,1† James
Troendle,2 João P. Souza,3 Olufemi
T. Oladapo4
1 Xinhua Hospital, Shanghai Jiao Tong University
School of Medicine, Shanghai, China
2 National Heart, Lung, and Blood Institute, National
Institutes of Health, Bethesda, MD, U.S.A.
3 University of Sao Paulo, Sao Paulo, Brazil
4 UNDP-UNFPA-UNICEF-WHO-World Bank Special Programme
of Research, Development and Research Training in Human Reproduction
(HRP), Department of Sexual and Reproductive Health and Research, World
Health Organization, Geneva, Switzerland
† Corresponding author: Dr. Jun Zhang
Dr. Jun Zhang
Xinhua Hospital, Shanghai Jiao Tong University School of Medicine,
Shanghai, 200092, China.
E-mail: junjimzhang@sina.com
Word count: 490
Sir,
De Vries et al. used data simulation to create two datasets, based on
Friedman and Zhang labour curve models, respectively, to assess whether
repeated-measures polynomial regression and interval-censored regression
used by Zhang et al. are appropriate statistical methods to describe the
first stage of labour.1 It was concluded that these
methods do not accurately reflect the underlying data. We respectfully
disagree.
The key issue regarding the appropriateness of polynomial repeated
measures regression hinges on whether the shape of the average labour
curve matches the shape of the underlying individual curves. The authors
demonstrated that when vaginal examinations are performed 1-3 hourly or
more, the average labour curve is close to the underlying labour pattern
(Figures 3B, S4 and S5). We suggest that the authors show a similar
figure as Figures 3B and S4 with an increasing frequency of vaginal
examinations, to illustrate how close the average curve becomes to the
underlying labour pattern when the underlying labour pattern is assumed
to be progressively accelerating. This evidence indicate that the
polynomial regression is a reasonable method to model the labour curve
when vaginal examinations are performed at least 1-3 hourly.
Labour patterns vary widely from woman to woman. Any single labour curve
cannot truly represent the reality. Friedman curve is an idealized
individual curve. The rigid one curve for all is too simplistic and has
important clinical consequences. Whether the true active phase of labour
follows a straight line or exponential curve still remains undetermined.
Both trajectories, as well as other patterns, are likely to co-exist.
Thus, it may not be totally accurate to use the piecewise linear curve
as the gold standard to judge the appropriateness of a statistical
method.
The estimate of labour duration, particularly the 95thcentile, is influenced by the distribution of the transit time. While
Figure 1 demonstrated the approximate log normal distribution of the
latent phase, active phase and total duration, it is also important to
show such a distribution in each cm-by-cm segment with varying frequency
of vaginal examinations. If the distribution is not log normal, the
estimate may be biased. In addition, it is overly simplistic to assume
that every parturient enters the active phase of labour at 4 cm
dilatation, which has been objected by Cohen and
Friedman2. Such an assumption is likely to result in
substantially reduced variations of the average labour duration.
Subsequently, the 95th centiles based on the simulated
data are much smaller than those based on the real
data1 (Table 1). Oladapo et al. used a multistate
Markov model and produced very similar results as the interval censored
regression3, suggesting that the simulated data may be
inappropriate to provide realistic results that have much greater
variations than the simulated data have.
Nonetheless, we agree that the admission time to labour may bias the
results of the latent phase due to potential selection bias. We had
ignored the findings before 3 cm of cervical dilatation for the same
reason4.
CONFLICT OF INTEREST
None declared. Completed disclosure of interests form available to view
online as supporting information