Predicting outcomes in radiation oncology-multifactorial decision support systems

被引:305
作者
Lambin, Philippe [1 ]
van Stiphout, Ruud G. P. M. [1 ]
Starmans, Maud H. W. [1 ]
Rios-Velazquez, Emmanuel [1 ]
Nalbantov, Georgi [1 ]
Aerts, Hugo J. W. L. [2 ,3 ]
Roelofs, Erik [1 ]
van Elmpt, Wouter [1 ]
Boutros, Paul C. [4 ]
Granone, Pierluigi [5 ]
Valentini, Vincenzo [6 ]
Begg, Adrian C. [7 ]
De Ruysscher, Dirk [1 ]
Dekker, Andre [1 ]
机构
[1] Maastricht Univ Med Ctr, Dept Radiat Oncol MAASTRO, GROW Sch Oncol & Dev Biol, NL-6229 ET Maastricht, Netherlands
[2] Harvard Univ, Dana Farber Canc Inst, Dept Radiat Oncol, Boston, MA 02215 USA
[3] Harvard Univ, Dana Farber Canc Inst, Dept Biostat & Computat Biol, Boston, MA 02215 USA
[4] Ontario Inst Canc Res, Toronto, ON M5G 0A3, Canada
[5] Univ Cattolica Sacro Cuore, Policlin Univ Agostino Gemelli, Dept Surg, I-00168 Rome, Italy
[6] Univ Cattolica Sacro Cuore, Policlin Univ Agostino Gemelli, Dept Radiotherapy, I-00168 Rome, Italy
[7] Netherlands Canc Inst, Div Biol Stress Response, NL-1066 CX Amsterdam, Netherlands
关键词
CELL LUNG-CANCER; SINGLE NUCLEOTIDE POLYMORPHISMS; POSITRON-EMISSION-TOMOGRAPHY; GENE-EXPRESSION PROGRAMS; GENOME-WIDE ASSOCIATION; DOUBLE-STRAND BREAKS; TUMOR VOLUME; EXTERNAL VALIDATION; PROGNOSTIC-FACTOR; FDG-PET;
D O I
10.1038/nrclinonc.2012.196
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
With the emergence of individualized medicine and the increasing amount and complexity of available medical data, a growing need exists for the development of clinical decision-support systems based on prediction models of treatment outcome. In radiation oncology, these models combine both predictive and prognostic data factors from clinical, imaging, molecular and other sources to achieve the highest accuracy to predict tumour response and follow-up event rates. In this Review, we provide an overview of the factors that are correlated with outcome-including survival, recurrence patterns and toxicity-in radiation oncology and discuss the methodology behind the development of prediction models, which is a multistage process. Even after initial development and clinical introduction, a truly useful predictive model will be continuously re-evaluated on different patient datasets from different regions to ensure its population-specific strength. In the future, validated decision-support systems will be fully integrated in the clinic, with data and knowledge being shared in a standardized, instant and global manner. Lambin, P. et al. Nat. Rev. Clin. Oncol. 10, 27-40 (2013); published online 20 November 2012; doi:10.1038/nrclinonc.2012.196
引用
收藏
页码:27 / 40
页数:14
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