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Record W2755251616 · doi:10.3892/mco.2017.1419

Long-term outcomes of laparoscopy vs. open surgery for colorectal cancer in elderly patients: A meta-analysis

2017· article· en· W2755251616 on OpenAlexaboutno aff
Fugang Wang, Yu Zhaopeng, Zhao Wu Meng

Bibliographic record

VenueMolecular and Clinical Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisLaparoscopic surgeryLaparotomyLaparoscopyRandomized controlled trialColorectal cancerCochrane LibraryColorectal surgeryConfidence intervalConfoundingCancerAbdominal surgeryCohort studySurgeryInternal medicine

Abstract

fetched live from OpenAlex

The long-term outcome of laparoscopic surgery for geriatric patients with colorectal cancer remains unclear due to decreased functional reserves and increased medical comorbidities. A meta-analysis was performed in the present study to compare the long-term outcome between laparoscopy and laparotomy. Randomized controlled trials and comparative studies regarding laparoscopy vs. open surgery for colorectal cancer in elderly patients were searched in Pubmed, Embase, and Cochrane library between inception and April 20, 2017. The methodological quality of the cohort studies was evaluated using the Newcastle-Ottawa Scale. The meta-analysis was performed using Stata v12.0 software. Eight cohort studies were enrolled in the meta-analysis. Laparoscopic surgery was associated with a higher 3-year survival rate compared with open surgery [risk ratio (RR), 0.74; 95% confidence interval (CI), 0.61-0.90; P=0.003]. No significant difference was identified between laparoscopy and laparotomy regarding the 5-year survival rate (RR, 0.93; 95% CI, 0.78-1.11, P=0.424). The results of the meta-analysis indicated that the use of laparoscopic surgery on geriatric patients with colorectal cancer should be increased due to more improved long-term outcomes. All the studies included in the meta-analysis were case-control studies with selection bias and other confounding factors. Thus, larger sample sizes and multicenter randomized controlled trials are required to further validate the use of laparoscopic surgery as the preferred therapeutic option for elderly patients with colorectal cancer.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.168
GPT teacher head0.494
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations22
Published2017
Admission routes1
Has abstractyes

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