Evidence map›Paper›PMID 37072711›Full record

SynthesisBMC infectious diseases2023

Clinical outcomes of antimicrobial resistance in cancer patients: a systematic review of multivariable models.

Anders Skyrud Danielsen, Léa Franconeri, Samantha Page, Anders Eivind Myhre, Ragnhild Agathe Tornes, Oliver Kacelnik, Jørgen Vildershøj Bjørnholt

Abstract readSystematic Review
In one paragraph

Synthesis in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. IntestinalBMJ open · 2024
    Article
  10. Review
  11. Article
  12. Cancer and sepsis.Clinical science (London, England : 1979) · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Anders Skyrud DanielsenDepartment of Microbiology, Oslo University Hospital, Oslo, Norway. andersskyrud.danielsen@fhi.no.ORCID http://orcid.org/0000-0003-2006-2260
Léa FranconeriDepartment of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway.
Samantha PageDepartment of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway.
Anders Eivind MyhreDepartment of Haematology, Oslo University Hospital, Oslo, Norway.
Ragnhild Agathe TornesThe Library for the Healthcare Administration, Norwegian Institute of Public Health, Oslo, Norway.
Oliver KacelnikDepartment of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway.
Jørgen Vildershøj BjørnholtDepartment of Microbiology, Oslo University Hospital, Oslo, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInfections are major causes of disease in cancer patients and pose a major obstacle to the success of cancer care. The global rise of antimicrobial resistance threatens to make these obstacles even greater and hinder continuing progress in cancer care. To prevent and handle such infections, better models of clinical outcomes building on current knowledge are needed. This internally funded systematic review (PROSPERO registration: CRD42021282769) aimed to review multivariable models of resistant infections/colonisations and corresponding mortality, what risk factors have been investigated, and with what methodological approaches.

methodsWe employed two broad searches of antimicrobial resistance in cancer patients, using terms associated with antimicrobial resistance, in MEDLINE and Embase through Ovid, in addition to Cinahl through EBSCOhost and Web of Science Core Collection. Primary, observational studies in English from January 2015 to November 2021 on human cancer patients that explicitly modelled infection/colonisation or mortality associated with antimicrobial resistance in a multivariable model were included. We extracted data on the study populations and their malignancies, risk factors, microbial aetiology, and methods for variable selection, and assessed the risk of bias using the NHLBI Study Quality Assessment Tools.

resultsTwo searches yielded a total of 27,151 unique records, of which 144 studies were included after screening and reading. Of the outcomes studied, mortality was the most common (68/144, 47%). Forty-five per cent (65/144) of the studies focused on haemato-oncological patients, and 27% (39/144) studied several bacteria or fungi. Studies included a median of 200 patients and 46 events. One-hundred-and-three (72%) studies used a p-value-based variable selection. Studies included a median of seven variables in the final (and largest) model, which yielded a median of 7 events per variable. An in-depth example of vancomycin-resistant enterococci was reported.

conclusionsWe found the current research to be heterogeneous in the approaches to studying this topic. Methodological choices resulting in very diverse models made it difficult or even impossible to draw statistical inferences and summarise what risk factors were of clinical relevance. The development and adherence to more standardised protocols that build on existing literature are urgent.

Indexed as

Anti-Bacterial AgentsNeoplasmsDrug Resistance, BacterialHumansAnti-Bacterial AgentsAntimicrobial resistanceCancerInfectionMalignancyMortalityRisk factorsSystematic review

Identifiers

PMID37072711
PMCPMC10114324

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.