title: Predictive value of modelled tumour control probability based on individual measurements of in vitro radiosensitivity and potential doubling time.
abstract: OBJECTIVE
  The aim of this study was to compare patient-specific radiobiological parameters with population averages in predicting the clinical outcome after radiotherapy (RT) using a tumour control probability (TCP) model based on the biological effective dose (BED).
  
  
  METHODS
  A previously published study of 46 head and neck carcinomas with individually identified radiobiological parameters, radiosensitivity and potential doubling time (Tpot), and known tumour size was investigated. These patients had all been treated with external beam RT, and the majority had also received brachytherapy. The TCP for each individual based on the BED using patient-specific radiobiological parameters was compared with the TCP based on the BED using average radiobiological parameters (α=0.3 Gy(-1), Tpot=3 days).
  
  
  RESULTS
  43 patients remained in the final analysis. There was only a weak trend for increasing local tumour control with increasing BED in both groups. However, when the TCP was calculated, the use of patient-specific parameters was better for identifying local control correctly. The sensitivity and specificity for tumour-specific parameters were 63% and 80%, respectively. The corresponding values for population-based averages were 0% and 91%, respectively. The positive predictive value was 92% when tumour-specific parameters were used compared with 0% for population-based averages. A receiver operating characteristic curve confirmed the superiority of patient-specific parameters over population averages in predicting local control.
  
  
  CONCLUSIONS
  Individual radiobiological parameters are better than population-derived averages when used in a mathematical model to predict TCP after curative RT in head and neck carcinomas.
  
  
  CONCLUSIONS
  TCP based on individual radiobiological parameters is better than TCP based on population-based averages for identifying local control correctly.
authors.affiliation: Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden. mattias.hedman@karolinska.se
authors.forename: M
authors.initials: M
authors.lastname: Hedman
authors.forename: T
authors.initials: T
authors.lastname: Björk-Eriksson
authors.forename: O
authors.initials: O
authors.lastname: Brodin
authors.forename: I
authors.initials: I
authors.lastname: Toma-Dasu
mesh_terms: D002294:Carcinoma, Squamous Cell / Q000473:pathology / Q000532:radiotherapy*; D006258:Head and Neck Neoplasms / Q000473:pathology / Q000532:radiotherapy*; D006801:Humans; D066298:In Vitro Techniques; D008954:Models, Biological; D011237:Predictive Value of Tests; D012372:ROC Curve; D011836:Radiation Tolerance; D012062:Relative Biological Effectiveness; D012680:Sensitivity and Specificity; D016896:Treatment Outcome