A genetic algorithm for variable selection in logistic regression analysis of radiotherapy treatment outcomes

Medical Physics

Volumn 35, Issue 12, 2008, Pages 5426-5433

  Gayou, Olivier ^a,b   Das, Shiva K ^c   Zhou, Su Min ^c   Marks, Lawrence B ^d   Parda, David S ^a,b   Miften, Moyed ^e  

^a ALLEGHENY GENERAL HOSPITAL   (United States)

^b DREXEL UNIVERSITY COLLEGE OF MEDICINE   (United States)

^c DUKE UNIVERSITY MEDICAL CENTER   (United States)

^d UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^e UNIVERSITY OF COLORADO   (United States)

Author keywords

Genetic algorithm; Logistic regression; Radiobiological modeling; Variable selection

Indexed keywords

HOSPITAL DATA PROCESSING; LOGISTIC REGRESSION; PATIENT MONITORING; RADIOTHERAPY;

CROSSOVER AND MUTATION; INDIVIDUAL FACTORS; PATIENT POPULATION; RADIATION PNEUMONITIS; RADIOBIOLOGICAL MODELING; RADIOTHERAPY TREATMENT; STATISTICAL SIGNIFICANCE; VARIABLE SELECTION;

GENETIC ALGORITHMS;

ARTICLE; COMPUTER ASSISTED RADIOTHERAPY; CONTROLLED STUDY; GENETIC ALGORITHM; HUMAN; LUNG INJURY; LUNG NON SMALL CELL CANCER; MAJOR CLINICAL STUDY; PREDICTOR VARIABLE; PRIORITY JOURNAL; RADIATION PNEUMONIA; SMOKING HABIT; TREATMENT OUTCOME;

NICOTIANA TABACUM;

EID: 56749095591     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.3005974     Document Type: Article

References (24)

1. S. Webb and A. E. Nahum, " A model calculating tumor control probability in radiotherapy including the effects of inhomogeneous distributions of dose and clonogenic cell density.," Phys. Med. Biol. 38, 653-666 (1993).
2. B. C. Burman, G. J. Kutcher, B. Emami, and M. Goitein, " Fitting of normal tissue tolerance data to an analytic function.," Int. J. Radiat. Oncol., Biol., Phys. 21, 123-135 (1991).
3. J. T. Lyman, " Complication probability as assessed from dose-volume histograms.," Radiat. Res. 104, S13-S19 (1985).
4. B. Sanchez-Nieto and A. E. Nahum, " BIOPLAN: Software for the biological evaluation of radiotherapy treatment plans.," Med. Dosim. 25, 71-76 (2000).
5. B. Warkentin, P. Stavrev, N. Stavreva, C. Field, and B. G. Fallone, " A TCP-NTCP estimation module using DVHs and known radiobiological models and parameter sets.," Cryst. Prop. Prep. 5, 50-63 (2004).
6. S. Chen, S. Zhou, F.-F. Yin, L. B. Marks, and S. K. Das, " Using patient data similarities to predict radiation pneumonitis via a self-organizing map.," Phys. Med. Biol. 53, 203-216 (2008).
7. S. Chen, S. Zhou, F.-F. Yin, L. B. Marks, and S. K. Das, " Investigation of the support vector machine algorithm to predict lung radiation-induced pneumonitis.," Med. Phys. 34, 3808-3814 (2007).
8. S. Chen, S. Zhou, J. Zhang, F.-F. Yin, L. B. Marks, and S. K. Das, " A neural network model to predict lung radiation-induced pneumonitis.," Med. Phys. 34, 3420-3427 (2007).
9. S. K. Das " Predicting lung radiotherapy-induced pneumonitis using a model combining parametric lyman probit with nonparametric decision trees.," Int. J. Radiat. Oncol., Biol., Phys. 68, 1212-1221 (2006).
10. I. El Naqa, G. Suneja, P. E. Lindsay, A. G. Hope, J. R. Alaly, M. Vicic, J. D. Bradley, A. Apte, and J. O. Deasy, " Dose response explorer: An integrated open-source tool for exploring and modeling radiotherapy dose-volume outcome relationships.," Phys. Med. Biol. 51, 5719-5735 (2006).
11. O. Gayou, D. S. Parda, and M. Miften, " EUCLID: An outcome analysis tool for high-dimensional clinical studies.," Phys. Med. Biol. 52, 1705-1719 (2007).
12. I. El Naqa, J. Bradley, A. I. Bianco, P. E. Lindsay, M. Vicic, A. Hope, and J. O. Deasy, " Multivariate modeling of radiotherapy outcomes, including dose-volume and clinical factors.," Int. J. Radiat. Oncol., Biol., Phys. 64, 1275-1286 (2006).
13. Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs (Springer, New York, 1992).
14. M. Mitchell, An Introduction to Genetic Algorithms (MIT Press, Cambridge, MA, 1996).
15. D. A. Coley, An Introduction to Genetic Algorithms for Scientists and Engineers (World Scientific, London, 1999).
16. S. Vinterbo and L. Ohno-Machado, " A genetic algorithm to select variables in logistic regression: Example in the domain of myocardial infarction.," Proceedings of the 1999 AMIA Annual Symposium, pp. 984-988.
17. J. A. Hanley and B. J. McNeil, " A method of comparing the areas under receiver-operating characteristic curves derived from the same cases.," Radiology 148, 839-843 (1983).
18. M. L. Hernando, L. B. Marks, G. C. Bentel, S.-M. Zhou, D. Hollis, S. K. Das, M. Fan, M. T. Munley, T. D. Shafman, M. S. Anscher, and P. A. Lind, " Radiation-induced pulmonary toxicity: A dose-volume histogram analysis in 201 patients with lung cancer.," Int. J. Radiat. Oncol., Biol., Phys. 51, 650-659 (2001).
19. D. Etiz, L. B. Marks, S.-M. Zhou, G. C. Bentel, R. Clough, M. L. Hernando, and P. A. Lind, " Influence of tumor volume on survival in patients irradiated for non-small-cell lung cancer.," Int. J. Radiat. Oncol., Biol., Phys. 53, 835-846 (2002).
20. D. E. Matthews and V. T. Farewell, Using and Understanding Medical Statistics, 3rd ed. (Karger, Basel, Switzerland, 1996).
21. K. Nilsson, R. Henriksson, Y. Q. Cai, S. Hellström, S. Hörnqvist Bylunds, and L. Bjermer, " Effects of tobacco-smoke on radiation-induced pneumonitis in rats.," Int. J. Radiat. Biol. 62, 719-727 (1992).
22. S. Johansson, L. Bjermer, L. Franzen, and R. Henriksson, " Effects of ongoing smoking on the development of radiation-induced pneumonitis in breast cancer and oesophagus cancer patients.," Radiother. Oncol. 49, 41-47 (1998).
23. L. Bejmer, R. Hallgren, K. Nilsson, L. Franzen, T. Sandström, B. Särnstrand, and R. Henriksson, " Radiation-induced increase in hyaluronan and fibronectin in bronchoalveolar lavage fluid from breast cancer is suppressed by smoking.," Eur. Respir. J. 5, 785-790 (1992).
24. S. Forrest, " Genetic algorithms: Principles of natural selection applied to computation.," Science 261, 872-878 (1993).