ArticleCancers2019
Personalizing the Prediction of Colorectal Cancer Prognosis by Incorporating Comorbidities and Functional Status into Prognostic Nomograms.
Article in Cancers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Prognostic Effect of Performance Status on Outcomes of Patients with Colorectal Cancer Receiving First-Line Chemotherapy: A Meta-analysis.Journal of gastrointestinal cancer · 2024Pooled it
- Pooled it
- Impact of Comorbidities on Treatment Outcomes Among Saudi Patients With Colorectal Cancer: A Retrospective Study.Cureus · 2025Article
- Trends in the incidence, survival, and prognostic nomogram of angiosarcoma in the United States.Medicine · 2025Article
- In-hospital outcomes of older patients with gastric cancer and their risk factors: large comprehensive institution-based study.European geriatric medicine · 2024Article
- The Demographic Profile of Colorectal Cancer Patients in Indonesia: Insights from a Single Center Experience and Exploration of Immune Response and Survival Outcomes.F1000Research · 2024Article
- Machine Learning in Colorectal Cancer Risk Prediction from Routinely Collected Data: A Review.Diagnostics (Basel, Switzerland) · 2023Review
- Construction of a DDR-related signature for predicting of prognosis in metastatic colorectal carcinoma.Frontiers in oncology · 2023Article
- Prognostic Value of Comorbidity for Patients with Upper Tract Urothelial Carcinoma after Radical Nephroureterectomy.Cancers · 2022Article
- Extramural vascular invasion nomogram before radical resection of rectal cancer based on magnetic resonance imaging.Frontiers in oncology · 2022Article
- Article
- A Novel Prognostic Model and Practical Nomogram for Predicting the Outcomes of Colorectal Cancer: Based on Tumor Biomarkers and Log Odds of Positive Lymph Node Scheme.Frontiers in oncology · 2021Article
- An Oxidative Stress Index-Based Score for Prognostic Prediction in Colorectal Cancer Patients Undergoing Surgery.Oxidative medicine and cellular longevity · 2021Article
- Whole blood DNA methylation aging markers predict colorectal cancer survival: a prospective cohort study.Clinical epigenetics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Despite consistent evidence that comorbidities and functional status (FS) are strong prognostic factors for colorectal cancer (CRC) patients, these important characteristics are not considered in prognostic nomograms. We assessed to what extent incorporating these characteristics into prognostic models enhances prediction of CRC prognosis. CRC patients diagnosed in 2003-2014 who were recruited into a population-based study in Germany and followed over a median time of 4.7 years were randomized into training (
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.