Q (sonnet-5.5): In colorectal cancer do patients with microsatellite instability in the TCGA dataset have a similar prognosis as those in the MSK Gastroenterology 2020 study? ▶ read_guide { "uri": "cbioportal://statistical-tests-guide" } ▶ list_studies { "search": "colorectal", "limit": 50 } ◀ result Statistical Test Selection Guide ================================ Purpose ------- This guide ensures the correct statistical test is selected before performing any group comparison, matching cBioPortal's own Group Comparison defaults. HARD RULES — NEVER FABRICATE A STATISTIC ---------------------------------------- ClickHouse cannot run statistical tests. The agent therefore must NEVER produce a derived statistic that is not a literal column value from a SQL result. Specifically: 1. **Never invent a p-value.** Not "p < 0.001", not "p ≈ 0.05", not any p-value. If the user asks "what is the p-value?", the answer is *"I can't compute that — here is the 2x2 contingency table (or group statistics). Run it in cBioPortal's Group Comparison tab, in R with `fisher.test(...)` / `wilcox.test(...)`, or in Python with `scipy.stats.fisher_exact(...)` / `mannwhitneyu(...)`."* 2. **Never claim mutual exclusivity (or co-occurrence) from a contingency table alone.** A 2x2 table is not a test. The shape "altered/not altered × group A/group B" needs Fisher's exact + a defined direction (odds ratio < 1 with significant p). Without that test, the agent presents the table and stops. Descriptive phrasing is also a claim: "largely/mostly mutually exclusive", "rarely co-occur", "tend to co-occur" are forbidden without the test — point to cBioPortal's Mutual Exclusivity tab instead. 3. **Never report a "median" that came from `AVG(...)` or any non-median aggregate.** "Median" and "mean" are different statistics; for skewed clinical distributions (especially survival) they differ substantially. Use ClickHouse's `quantile(0.5)(...)` for actual median, and label arithmetic averages as "mean", never "median". 4. **Never report a hazard ratio, odds ratio, risk ratio, or relative risk** that wasn't computed by an external tool. These require regression / model fitting that ClickHouse does not do. 5. **Never report median overall survival from `AVG(OS_MONTHS)` or even `quantile(0.5)(OS_MONTHS)`.** Median OS requires Kaplan-Meier estimation, which handles censoring (`OS_STATUS = 0:LIVING` means the event hasn't happened yet). Naive medians/means over `OS_MONTHS` ignore censoring and are systematically wrong. The correct handoff: return the raw `(OS_MONTHS, OS_STATUS)` pairs (or descriptive counts: N events, N censored, follow-up range) and tell the user to run KM in R (`survival::survfit`) or Python (`lifelines.KaplanMeierFitter`), or use cBioPortal's Survival comparison. If asked to do any of (1)–(5), respond with the appropriate handoff template from the "Approved Response Templates" section below — do not produce the number. Ambiguous-Term Clarification (before any analysis) -------------------------------------------------- If the user's question uses an ambiguous term, ask before computing anything. Examples: - **"aggressive"** → could mean shorter overall survival, higher metastasis rate, higher grade/stage, higher TMB, or specific molecular features. Ask which definit … (9984 more chars) ◀ result {"result":[{"cancer_study_identifier":"msk_met_2021","name":"MSK MetTropism (MSK, Cell 2021)","type_of_cancer_id":"mixed","sample_count":25775,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=msk_met_2021"},{"cancer_study_identifier":"crc_msk_2026","name":"Colorectal Adenocarcinoma (MSK, 2026)","type_of_cancer_id":"read","sample_count":7237,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=crc_msk_2026"},{"cancer_study_identifier":"crc_eo_2020","name":"Colorectal Cancer (MSK, JNCI 2021)","type_of_cancer_id":"bowel","sample_count":1516,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=crc_eo_2020"},{"cancer_study_identifier":"crc_msk_2017","name":"Metastatic Colorectal Cancer (MSK, Cancer Cell 2018)","type_of_cancer_id":"coadread","sample_count":1134,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=crc_msk_2017"},{"cancer_study_identifier":"crc_sysucc_2022","name":"Colorectal Cancer- ChangKang Project (SYSUCC, Nat Commun 2022)","type_of_cancer_id":"coadread","sample_count":1015,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=crc_sysucc_2022"},{"cancer_study_identifier":"coadread_tcga","name":"Colorectal Adenocarcinoma (TCGA, Firehose Legacy)","type_of_cancer_id":"coadread","sample_count":640,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=coadread_tcga"},{"cancer_study_identifier":"coadread_dfci_2016","name":"Colorectal Adenocarcinoma (DFCI, Cell Reports 2016)","type_of_cancer_id":"coadread","sample_count":619,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=coadread_dfci_2016"},{"cancer_study_identifier":"coadread_tcga_pan_can_atlas_2018","name":"Colorectal Adenocarcinoma (TCGA, PanCancer Atlas)","type_of_cancer_id":"coadread","sample_count":594,"has_guide":true,"url":"https://www.cbioportal.org/study/summary?id=coadread_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"crc_apc_impact_2020","name":"Colorectal Cancer (MSK, Gastroenterology 2020)","type_of_cancer_id":"coadread","sample_count":471,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=crc_apc_impact_2020"},{"cancer_study_identifier":"coadread_tcga_pub","name":"Colorectal Adenocarcinoma (TCGA, Nature 2012)","type_of_cancer_id":"coadread","sample_count":276,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=coadread_tcga_pub"},{"cancer_study_identifier":"bowel_colitis_msk_2022","name":"Colorectal Adenocarcinoma (MSK, Nat Commun 2022)","type_of_cancer_id":"bowel","sample_count":179,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=bowel_colitis_msk_2022"},{"cancer_study_identifier":"coadread_cass_2020","name":"Colorectal Cancer (CAS Shanghai, Cancer Cell 2020)","type_of_cancer_id":"coadread","sample_count":146,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=coadread_cass_2020"},{"cancer_study_identifier":"coadread_mskcc","name":"Colorectal Adenocarcinoma Triplets (MSK, Geno … (2148 more chars) ═ answer (success) "TCGA" matches three colorectal studies in cBioPortal, so I need to know which one you want before I compare anything. - **Colorectal Adenocarcinoma (TCGA, PanCancer Atlas)** (`coadread_tcga_pan_can_atlas_2018`): 594 samples - **Colorectal Adenocarcinoma (TCGA, Firehose Legacy)** (`coadread_tcga`): 640 samples - **Colorectal Adenocarcinoma (TCGA, Nature 2012)** (`coadread_tcga_pub`): 276 samples The MSK study is unambiguous. It is [Colorectal Cancer (MSK, Gastroenterology 2020)](https://www.cbioportal.org/study/summary?id=crc_apc_impact_2020) (`crc_apc_impact_2020`), with 471 samples. I also need you to confirm what "prognosis" means here. I'd assume overall survival (OS), but I can use disease-free survival (DFS) or another endpoint if you prefer. A survival comparison needs Kaplan-Meier curves and a log-rank test. I can't compute those myself. What I can do is pull the following for each cohort: - the number of MSI patients - the number of deaths and the number of censored patients - the follow-up range I'd then link you to cBioPortal's Group Comparison Survival tab, where you can run the test. Which TCGA study should I use? I can also use all three. And is OS the right endpoint?