Advanced

Prognostic models for outcome following liver resection for colorectal cancer metastases: A systematic review.

Spelt, Lidewij LU ; Andersson, Bodil LU ; Nilsson, J and Andersson, Roland LU (2012) In European Journal of Surgical Oncology 38. p.16-24
Abstract
BACKGROUND: Liver resection provides the best chance for cure in colorectal cancer (CRC) liver metastases. A variety of factors that might influence survival and recurrence have been identified. Predictive models can help in risk stratification, to determine multidisciplinary treatment and follow-up for individual patients. AIMS: To systematically review available prognostic models described for outcome following resection of CRC liver metastases and to assess their differences and applicability. METHODS: The Pubmed, Embase and Cochrane Library databases were searched for articles proposing a prognostic model or risk stratification system for resection of CRC liver metastases. Search terms included 'colorectal', 'liver', 'metastasis',... (More)
BACKGROUND: Liver resection provides the best chance for cure in colorectal cancer (CRC) liver metastases. A variety of factors that might influence survival and recurrence have been identified. Predictive models can help in risk stratification, to determine multidisciplinary treatment and follow-up for individual patients. AIMS: To systematically review available prognostic models described for outcome following resection of CRC liver metastases and to assess their differences and applicability. METHODS: The Pubmed, Embase and Cochrane Library databases were searched for articles proposing a prognostic model or risk stratification system for resection of CRC liver metastases. Search terms included 'colorectal', 'liver', 'metastasis', 'resection', 'prognosis' and 'prediction'. The articles were systematically reviewed. RESULTS: Fifteen prognostic systems were identified, published between 1996 and 2009. The median study population was 305 patients and the median follow-up was 32 months. All studies used Cox proportional hazards for multi-variable analysis. No prognostic factor was common in all models, though there was a tendency towards the number of metastases, CRC spread to lymph nodes, maximum size of metastases, preoperative CEA level and extrahepatic spread as representing independent risk factors. Seven models assigned more weight to selected factors considered of higher predictive value. CONCLUSION: The existing predictive models are diverse and their prognostic factors are often not weighed according to their impact. For the development of future predictive models, the complex relations within datasets and differences in relevance of individual factors should be taken into account, for example by using artificial neural networks. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
European Journal of Surgical Oncology
volume
38
pages
16 - 24
publisher
Elsevier
external identifiers
  • wos:000299608700004
  • pmid:22079259
  • scopus:83955165369
ISSN
1532-2157
DOI
10.1016/j.ejso.2011.10.013
language
English
LU publication?
yes
id
3f64d623-f023-49b8-b6eb-64792a669eda (old id 2220830)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/22079259?dopt=Abstract
date added to LUP
2011-12-02 21:11:31
date last changed
2017-09-17 08:09:12
@article{3f64d623-f023-49b8-b6eb-64792a669eda,
  abstract     = {BACKGROUND: Liver resection provides the best chance for cure in colorectal cancer (CRC) liver metastases. A variety of factors that might influence survival and recurrence have been identified. Predictive models can help in risk stratification, to determine multidisciplinary treatment and follow-up for individual patients. AIMS: To systematically review available prognostic models described for outcome following resection of CRC liver metastases and to assess their differences and applicability. METHODS: The Pubmed, Embase and Cochrane Library databases were searched for articles proposing a prognostic model or risk stratification system for resection of CRC liver metastases. Search terms included 'colorectal', 'liver', 'metastasis', 'resection', 'prognosis' and 'prediction'. The articles were systematically reviewed. RESULTS: Fifteen prognostic systems were identified, published between 1996 and 2009. The median study population was 305 patients and the median follow-up was 32 months. All studies used Cox proportional hazards for multi-variable analysis. No prognostic factor was common in all models, though there was a tendency towards the number of metastases, CRC spread to lymph nodes, maximum size of metastases, preoperative CEA level and extrahepatic spread as representing independent risk factors. Seven models assigned more weight to selected factors considered of higher predictive value. CONCLUSION: The existing predictive models are diverse and their prognostic factors are often not weighed according to their impact. For the development of future predictive models, the complex relations within datasets and differences in relevance of individual factors should be taken into account, for example by using artificial neural networks.},
  author       = {Spelt, Lidewij and Andersson, Bodil and Nilsson, J and Andersson, Roland},
  issn         = {1532-2157},
  language     = {eng},
  pages        = {16--24},
  publisher    = {Elsevier},
  series       = {European Journal of Surgical Oncology},
  title        = {Prognostic models for outcome following liver resection for colorectal cancer metastases: A systematic review.},
  url          = {http://dx.doi.org/10.1016/j.ejso.2011.10.013},
  volume       = {38},
  year         = {2012},
}