In the
field of meta-analysis methodology, some controversies are debated even too
much while other issues continue to be neglected.
The
controversy about the ôroleö of heterogeneity has been addressed by even too
many papers, and the very specialized article by Ioannidis at el.[1] confirms
this impression.
On the
other hand, the argument that the end-point of survival over time can appropriately
be handled only by methods accounting for the duration of the follow-up is
universally accepted in clinical trials, but is nearly universally neglected by
meta-analysis specialists. In the field of clinical trials, no study where
follow-up is extended over years presents the survival results as
time-independent crude death rates because the classical Kaplan-Meier survival
graph is always adopted. In contrast, in the context of meta-analyses,
the role of the follow-up duration is generally left out, and so crude rates
are nearly always the only basis for analysing and interpreting the
results.
The
tendency of meta-analysis experts to neglect how follow-up can be incorporated
into the meta-analytic survival assessment is confirmed by the paper of
Ioannidis at el. [1]: in fact the meta-analysis on colorectal cancer by
Golfinopoulos et al. [2], chosen by Ioannidis et al.[1] as a worked
example for debating methodological controversies, is a typical case where the
original studies used Kaplan-Meier curves (and not crude death rates) whereas
the meta-analysis used crude rates (with no adjustment for the follow-up
duration); nonetheless, a number of methodological controversies are debated by
Ioannidis et al.[1] with reference to this therapeutic problem, but not the
issue of incorporating the follow-up into the pooled analysis.
The above
considerations are intended to be a sort of encouragement so that, in the
next future, survival meta-analyses can incorporate the
follow-up duration into their assessment much more frequently than is currently
done.
Of course,
discussing the methodology of survival meta-analysis is beyond the purposes of
this Rapid Response. There is however another methodological point that
has so far been neglected although it could deserve, in our view, more
consideration.
It is
generally thought that survival meta-analysis based on individual patient data
is the gold standard in this field [3-7]. Consequently, when individual patient
data are unavailable, the only methodological choice is generally thought to be
the analysis of crude rates (with no adjustment for the duration of follow-up).
There is
however one intermediate option [8,9] between the survival meta-analysis of
individual patient data and the meta-analysis of crude survival rates with no
adjustment for the follow-up duration.
This
intermediate option is given by methods [8,9] that analyse the
Kaplan-Meier graph of the original clinical studies (using an appropriate
software [9]) and reconstruct the individual survival times from the downward
steps of the curve (along with other relevant survival information available
from the original study). In this way, a meta-analysis based on aggregate data
can be converted into a survival meta-analysis of individual patient data.
Numerous
studies have adopted this ôintermediateö approach [8,10-15], but the majority
of survival meta-analyses are still employing methods that disregard the
duration of the follow-up. As an example of the ôintermediateö approach, a real
data set [16] is shown in which the original Kaplan-Meier curve (Figure
1, Panel A) is compared with the Kaplan-Meier curve determined from the
survival times reconstructed by the specific software (Figure 1, Panel B).
Figure 1. Panel A shows the original Kaplan-Meier curve of the 68 recipients of a left ventricular assistance device calculated from the “real” survival times and published by Park et al [16]. The graphical analysis of the curve of Panel A, carried out by the specific software[9], generated the following “reconstructed” survival times: 3 months (n=18), 6 months (n=9), 9 months (n=3), 12 months (n=2), 15 months (n=4), 18 months (n=5), 24 months (n=4), 30 months (n=9), 39 months (n=1), 42 months (n=2) with 11 survivors at the closure of the study. The reconstructed survival times for the 68 patients generate the Kaplan-Meier curve shown in Panel B
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