Conceptio › Archive › ClinicalTrials.gov
ClinicalTrials.gov public full text Public Domain

Multicenter Observational Study Taulí-T1 Classification for the Management of pT1 Rectal Adenocarcinoma

Corporacion Parc Tauli · 2023
ClinicalTrials.gov · Datasets · License: Public Domain · 2023
Open Source ↗
tem
BACKGROUND: Rectal cancer is the sixth most common neoplasm in Spain. In the early stages (pT1-N0), the treatment of choice is transanal endoscopic microsurgery. Treatment may be expanded to radical surgery if there are poor prognostic factors for the presence of metastatic lymph nodes and a risk of recurrence (up to 29%). The most determining histopathological factor is the degree of submucosal invasion. There are different classical classifications to assess this invasion, which pose difficulties in establishing objective and reproducible measurements. Casalots et al. propose a new classification (Taulí-T1) based on the measurement of residual healthy submucosa (hrSB), hypothesizing that a greater amount of healthy submucosa correlates with a better prognosis. Results show less healthy submucosa in the recurrence group, with a trend towards statistical significance (p=0.09). OBJECTIVE: To compare the Taulí-T1 classification with conventional quantitative classifications (Kitajima, Ueno) and qualitative classifications (sm1, sm2, and sm3 by Kudo and Kikuchi). METHODOLOGY: A multicenter observational retrospective cohort study comparing the Taulí-T1 classification with classical classifications in 317 patients with stage pT1 rectal adenocarcinoma, following the STROBE guidelines. The main variable is the measurement of tumor invasion in µm through hrSB, compared to the invasion of quantitative (Kitajima and Ueno) and qualitative (Kudo and Kikuchi) classical classifications. Concordance will be assessed with the intraclass correlation coefficient for quantitative variables and Cohen's weighted kappa for qualitative variables, with a 95% confidence interval and p\<0.005.
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 1029745
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive