Projects per year
Abstract
Prediction models allow accurate estimate of individualized prognosis. Increasing numbers of models on survival of CRC patients with surgical resection are being published. However, their performance and potential clinical utility have been unclear. A systematic search in MEDLINE and Embase databases (until 9th April 2018) was performed. Original model development studies and external validation studies predicting any survival outcomes from CRC (follow up ≥1 year after surgery) were included. We conducted random-effects meta analyses in external validation studies to estimate the performance of each model. A total of 83 original prediction models and 52 separate external validation studies were identified. We identified five models (Basingstoke score, Fong score, Nordinger score, Peritoneal Surface Disease Severity Score and Valentini nomogram) that were validated in at least two external datasets with a median summarized C-statistic of 0.67 (range: 0.57–0.74). These models can potentially assist clinical decision-making. There is a pressing need for more external validation studies so as to evaluate the performance of other abundant published prediction models that have not been adequately validated. Future research should also focus on investigating the real-word impact and cost effectiveness of existing prediction models for CRC prognosis in clinical practice.
Original language | English |
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Pages (from-to) | 196-202 |
Number of pages | 7 |
Journal | Surgical Oncology |
Volume | 29 |
Early online date | 20 May 2019 |
DOIs | |
Publication status | Published - Jun 2019 |
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Dive into the research topics of 'Performance of prediction models on survival outcomes of colorectal cancer with surgical resection: A systematic review and meta-analysis'. Together they form a unique fingerprint.Projects
- 3 Finished
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MC_UU_00007/1 Genetic approaches to combating colorectal cancer
Dunlop, M. (Principal Investigator)
1/04/18 → 31/03/23
Project: Research
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Colorectal cancer reduction through risk stratification of screening, follow-up and treatment
Theodoratou, E. (Principal Investigator)
1/05/17 → 30/04/23
Project: Research
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Integrative Genomics in Colorectal Cancer Susceptibility:Developing risk reducing interventions through understanding biology
Dunlop, M. (Principal Investigator), Campbell, H. (Co-investigator), Farrington, S. (Co-investigator) & Theodoratou, E. (Co-investigator)
1/01/16 → 31/05/21
Project: Research