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Role of adjuvant therapy in esophageal cancer patients after neoadjuvant therapy and curative esophagectomy: A systematic review and meta-analysis.

2021· review· en· W3167330796 on OpenAlexaff
Yung Lee, Yasith Samarasinghe, Michael H. Lee, Luxury Thiru, Yaron Shargall, Christian Finley, Waël C. Hanna, Oren Levine, Rosalyn A. Juergens, John Agzarian

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typereview
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsJuravinski Cancer CentreUniversity of TorontoMcMaster University
Fundersnot available
KeywordsMedicineNeoadjuvant therapyEsophageal cancerEsophagectomyAdjuvant therapyMeta-analysisInternal medicineRadiation therapySubgroup analysisOncologyChemoradiotherapySurgeryGrading (engineering)CancerBreast cancer

Abstract

fetched live from OpenAlex

e16083 Background: While neoadjuvant therapy followed by esophagectomy is the standard of care for locally advanced esophageal cancer, the role of adjuvant therapy is uncertain. As such, this review aims to analyze esophageal cancer patients who previously underwent neoadjuvant therapy followed by a curative resection (negative margins) to determine whether additional adjuvant therapy is associated with improved survival outcomes. Methods: MEDLINE, EMBASE, and CENTRAL databases were searched up to August 2020 for studies comparing patients with esophageal cancer who underwent neoadjuvant therapy and curative resection with and without adjuvant therapy. Primary outcome was overall survival (OS), and secondary outcomes were disease-free survival (DFS), locoregional recurrence, and distant recurrence at 1 and 5-years. Random effects meta-analysis was conducted where appropriate. Grading of recommendations, assessment, development, and evaluation (GRADE) was used to assess the certainty of evidence. Results: Ten studies involving 6,462 patients were included. 6,162 (95.36%) patients from 7 studies received adjuvant chemotherapy, whereas 296 (4.58%) patients from 3 studies underwent either adjuvant radiotherapy or chemoradiotherapy. When compared to patients who received neoadjuvant therapy and esophagectomy alone, adjuvant therapy groups experienced a significant overall survival benefit by 48% at 1-year (RR 0.52, 95%CI 0.41-0.65, P < 0.001, moderate certainty). This reduction in mortality was consistent at long-term 5-year follow-up (RR 0.91, 95%CI 0.87-0.96, P < 0.001, moderate certainty). Subgroup analysis on pathologic node positive patients demonstrated a consistent survival benefit at 1-year (RR 0.57, 95% CI 0.42-0.77, P < 0.001, moderate certainty) and 5-year (RR 0.89 95%CI 0.84-0.95, P < 0.001, moderate certainty). While adjuvant therapy presented no benefit for the T0-2 stage subgroup, patients with T3-4 disease experienced a significant reduction in mortality with the addition of adjuvant therapy at both 1-year (RR 0.51, 95% CI 0.41-0.63, P < 0.001, moderate certainty), and 5-years (RR 0.91, 95% CI 0.85-0.97, P = 0.005, moderate certainty). Due to incomplete reporting, the added benefit of adjuvant therapy was uncertain regarding DFS, locoregional recurrence, and distant recurrence. Conclusions: Adjuvant therapy after neoadjuvant treatment and curative esophagectomy provides improved OS at 1 and 5 years, but the benefit for DFS and locoregional/distant recurrence was uncertain due to limited reporting of these outcomes.

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)0.012
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.027
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.032
Bibliometrics0.0040.006
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.217
GPT teacher head0.529
Teacher spread0.312 · 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 designMeta-analysis
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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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