Dear Nelly,
You could do this, at least in principle, if all proportions refer to
the same timepoint, for example 5 years. The problem is that the data
you obtain from studies with a time-to-event endpoint are different from
those that directly provide a five-year survival proportion: The
time-to-event analysis accounts for censoring, while the proportion of
living after five years relatively to all patients at baseline usually
does not account for censoring or missing data (and thus may
underestimate the true proportion).
If I understand you correctly, you want to pool survival proportions
(single-arm), not hazard ratios (comparing two arms).
The technical thing is that you have survival proportions with standard
error from the time-to-event studies and single proportions (survived/n)
from other studies. Survival proportions with standard errors can be
pooled usingthe generic inverse variance method. Proportions are best
be pooled using generalized linear models. See, for example, the
examples for function metaprop() in R package meta.
Best,
Gerta
Am 19.05.2020 um 14:15 schrieb ne gic:
Dear List,
From time to event data, it's common to calculate a combined HR for
instance from included studies - this I understand.
Does it make sense to perform a meta-analysis of the proportion (%) one
gets from overall time survival e.g. Overall 5y survival? imagine a
scenario where different studies are reporting different proportions of
patients surviving at this time point and I want to report a summary
proportion from all the studies at this time point.
If this is possible, does just collecting the proportion at that time
e.g. 5 year suffice as the data to use for this calculation? Or what
you suggest? Haven't seen a package that just takes a proportion.
Sincerely,
nelly
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