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Record W4322742511 · doi:10.3390/curroncol30030224

Therapeutic Strategies and Oncological Outcome of Peritoneal Metastases from Lung Cancer: A Systematic Review and Pooled Analysis

2023· review· en· W4322742511 on OpenAlexvenueno aff
Leandro Siragusa, Sara Di Carlo, Alessia Fassari, Bruno Sensi, Camilla Riccetti, Luciano Izzo, Giuseppe Cavallaro, Enrico Fiori, Paolo Sapienza, Letizia Mallia, Graziano Pernazza, Simone Sibio

Bibliographic record

VenueCurrent Oncology · 2023
Typereview
Languageen
FieldMedicine
TopicIntraperitoneal and Appendiceal Malignancies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLung cancerInclusion and exclusion criteriaPeritoneal carcinomatosisCytoreductive surgeryCancerIncidence (geometry)OncologySurgeryInternal medicineColorectal cancerPathologyAlternative medicineOvarian cancer

Abstract

fetched live from OpenAlex

The peritoneum is an unusual site of metastases from lung cancer, and optimal management at the moment remains unclear and mostly based on palliative strategies. Therefore, the aim of the study was to investigate demographic characteristics, management and overall survival of patients with peritoneal metastases from lung cancer (PCLC). A PRISMA-compliant systematic review and pooled analysis was performed searching all English studies published until December 2022. PROSPERO, CRD42022349362. Inclusion criteria were original articles including patients with peritoneal carcinomatosis from lung cancer, specifying at least one outcome of interest. Exclusion criteria were being unable to retrieve patient data from articles, and the same patient series included in different studies. Among 1746 studies imported for screening, twenty-one were included (2783 patients). Mean overall survival was between 0.5 and 5 months after peritoneal carcinomatosis diagnosis and 9 and 21 months from lung cancer diagnosis. In total, 27% of patients underwent first-line or palliative chemotherapy and 7% of them surgery. Management differs significantly among published studies. The literature on PCLC is scarce. Its incidence is low but appears to be substantially rising and is likely to be an underestimation. Prognosis is very poor and therapeutic strategies have been limited and used in a minority of patients. Subcategories of PCLC patients may have an improved prognosis and may benefit from an aggressive oncological approach, including cytoreductive surgery. Further investigation would be needed in this regard.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.527
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0100.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.218
GPT teacher head0.501
Teacher spread0.283 · 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.

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

Citations6
Published2023
Admission routes1
Has abstractyes

Explore more

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