% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Gambichler:302018,
author = {T. Gambichler and S. S. Weyer-Fahlbusch and J. Overbeck and
N. Abu Rached and J. Becker$^*$ and L. Susok},
title = {{I}mpaired {O}verall {S}urvival of {M}elanoma {P}atients
{D}ue to {A}ntibiotic {U}se {P}rior to {I}mmune {C}heckpoint
{I}nhibitor {T}herapy: {S}ystematic {R}eview and
{M}eta-{A}nalysis.},
journal = {Cancers},
volume = {17},
number = {11},
issn = {2072-6694},
address = {Basel},
publisher = {MDPI},
reportid = {DKFZ-2025-01216},
pages = {1872},
year = {2025},
abstract = {Background: The gut microbiome plays a pivotal role in
shaping systemic immunity and modulating anti-tumor
responses. Preclinical and clinical studies have shown that
higher gut microbial diversity and the presence of specific
commensal taxa correlate with improved responses to immune
checkpoint inhibitors (ICI) in melanoma. Conversely,
broad-spectrum antibiotics can induce dysbiosis, reducing T
cell activation and cytokine production, and have been
linked to diminished ICI efficacy in several cancer types.
Methods: We conducted a systematic review and meta-analysis
of seven retrospective cohorts (total n = 5213) comparing
overall survival in cutaneous melanoma (CM) patients who did
or did not receive systemic antibiotics within six weeks
before ICI initiation. From each study, we extracted hazard
ratios (HRs) for death, antibiotic-to-ICI interval, ICI
regimen (PD-1 monotherapy vs. PD-1 + CTLA-4 combination),
cohort size, and country. Pooled log-HRs were estimated
under fixed-effect and random-effects (REML) models.
Statistical heterogeneity was quantified by Cochran's Q and
I2 statistics, and τ2. We performed leave-one-out
sensitivity analyses, generated a Baujat plot to identify
influential studies, applied trim-and-fill to assess
publication bias, and ran meta-regressions for regimen,
antibiotic timing, sample size, and geography. Results:
Under the fixed-effect model, antibiotic exposure
corresponded to a pooled HR of 1.26 $(95\%$ CI 1.13-1.41; p
< 0.001). The random-effects model yielded a pooled HR of
1.55 $(95\%$ CI 1.21-1.98; p = 0.0005) with substantial
heterogeneity (Q = 25.1; I2 = $76\%).$ Prediction intervals
(0.78-3.06) underscored between-study variability.
Leave-one-out analyses produced HRs from 1.50 to 1.75,
confirming robustness, and the Baujat plot highlighted two
cohorts as primary heterogeneity drivers. Trim-and-fill
adjusted the HR to 1.46 $(95\%$ CI 1.08-1.97). In subgroup
analyses, combination therapy studies (k = 4) showed a
pooled HR of ~1.9 (I2 = $58\%)$ versus ~1.3 (I2 = $79\%)$
for monotherapy. Meta-regression attributed the largest
variance to the regimen (R2 = $32\%;$ β(monotherapy) =
-0.35; p = 0.13). Conclusions: Pre-ICI antibiotic use in CM
is consistently associated with a $26-55\%$ increase in
mortality risk, particularly with PD-1 + CTLA-4
combinations, reinforcing the mechanistic link between
microbiome integrity and ICI success. Looking ahead,
integrating prospective microbiome profiling into clinical
trials will be critical to personalize ICI therapy, clarify
causality, and identify microbial biomarkers for optimal
treatment selection. Prospective, microbiome-integrated
trials promise to refine melanoma immunotherapy by tailoring
antibiotic stewardship and microbial interventions to
enhance patient outcomes.},
subtyp = {Review Article},
keywords = {antibiosis (Other) / immunotherapy (Other) / infection
(Other) / ipilimumab (Other) / mortality (Other) / nivolumab
(Other) / pembrolizumab (Other)},
cin = {ED01},
ddc = {610},
cid = {I:(DE-He78)ED01-20160331},
pnm = {899 - ohne Topic (POF4-899)},
pid = {G:(DE-HGF)POF4-899},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:40507352},
doi = {10.3390/cancers17111872},
url = {https://inrepo02.dkfz.de/record/302018},
}