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Record W2990261978 · doi:10.1186/s12957-019-1754-x

Role of the intestinal microbiome in colorectal cancer surgery outcomes

2019· review· en· W2990261978 on OpenAlexaboutno aff
Lelde Lauka, Elisa Reitano, Maria Clotilde Carra, Federica Gaiani, Paschalis Gavriilidis, Francesco Brunetti, Gian Luigi de’Angelis, Iradj Sobhani, Nicola de’Angelis

Bibliographic record

VenueWorld Journal of Surgical Oncology · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineColorectal cancerFusobacterium nucleatumSurgical oncologyColorectal surgeryInternal medicineCohort studyCancerMicrobiomeOncologyGeneral surgerySurgeryBioinformaticsAbdominal surgery

Abstract

fetched live from OpenAlex

OBJECTIVES: Growing evidence supports the role of the intestinal microbiome in the carcinogenesis of colorectal cancers, but its impact on colorectal cancer surgery outcomes is not clearly defined. This systematic review aimed to analyze the association between intestinal microbiome composition and postoperative complication and survival following colorectal cancer surgery. METHODS: A systematic review was conducted according to the 2009 PRISMA guidelines. Two independent reviewers searched the literature in a systematic manner through online databases, including Medline, Scopus, Embase, Cochrane Oral Health Group Specialized Register, ProQuest Dissertations and Theses Database, and Google Scholar. Human studies investigating the association between the intestinal microbiome and the short-term (anastomotic leakage, surgical site infection, postoperative ileus) and long-term outcomes (cancer-specific mortality, overall and disease-free survival) of colorectal cancer surgery were selected. Patients with any stage of colorectal cancer were included. The Newcastle-Ottawa scale for case-control and cohort studies was used for the quality assessment of the selected articles. RESULTS: Overall, 8 studies (7 cohort studies and 1 case-control) published between 2014 and 2018 were included. Only one study focused on short-term surgical outcomes, showing that anastomotic leakage is associated with low microbial diversity and abundance of Lachnospiraceae and Bacteroidaceae families in the non-cancerous resection lines of the stapled anastomoses of colorectal cancer patients. The other 7 studies focused on long-term oncological outcomes, including survival and cancer recurrence. The majority of the studies (5/8) found that a higher level of Fusobacterium nucleatum adherent to the tumor tissue is associated with worse oncological outcomes, in particular, increased cancer-specific mortality, decreased median and overall survival, disease-free and cancer-specific survival rates. Also a high abundance of Bacteroides fragilis was found to be linked to worse outcomes, whereas the relative abundance of the Prevotella-co-abundance group (CAG), the Bacteroides CAG, and the pathogen CAG as well as Faecalibacterium prausnitzii appeared to be associated with better survival. CONCLUSIONS: Based on the limited available evidence, microbiome composition may be associated with colorectal cancer surgery outcomes. Further studies are needed to elucidate the role of the intestinal microbiome as a prognostic factor in colorectal cancer surgery and its possible clinical implications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0050.005
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.361
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations59
Published2019
Admission routes1
Has abstractyes

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