@article {55, title = {PET-based dose painting in non-small cell lung cancer: Comparing uniform dose escalation with boosting hypoxic and metabolically active sub-volumes.}, journal = {Radiother Oncol}, volume = {116}, year = {2015}, month = {2015 Aug}, pages = {281-6}, abstract = {

BACKGROUND AND PURPOSE: We compared two imaging biomarkers for dose-escalation in patients with advanced non-small cell lung cancer (NSCLC). Treatment plans boosting metabolically active sub-volumes defined by FDG-PET or hypoxic sub-volumes defined by HX4-PET were compared with boosting the entire tumour.

MATERIALS AND METHODS: Ten NSCLC patients underwent FDG- and HX4-PET/CT scans prior to radiotherapy. Three isotoxic dose-escalation plans were compared per patient: plan A, boosting the primary tumour (PTVprim); plan B, boosting sub-volume with FDG >50\% SUVmax (PTVFDG); plan C, boosting hypoxic volume with HX4 tumour-to-background >1.4 (PTVHX4).

RESULTS: Average boost volumes were 507 {\textpm} 466 cm(3) for PTVprim, 173 {\textpm} 127 cm(3) for PTVFDG and 114 {\textpm} 73 cm(3) for PTVHX4. The smaller PTVHX4 overlapped on average 87 {\textpm} 16\% with PTVFDG. Prescribed dose was escalated to 87 {\textpm} 10 Gy for PTVprim, 107 {\textpm} 20 Gy for PTVFDG, and 117 {\textpm} 15 Gy for PTVHX4, with comparable doses to the relevant organs-at-risk (OAR). Treatment plans are available online (https://www.cancerdata.org/10.1016/j.radonc.2015.07.013).

CONCLUSIONS: Dose escalation based on metabolic sub-volumes, hypoxic sub-volumes and the entire tumour is feasible. Highest dose was achieved for hypoxia plans, without increasing dose to OAR. For most patients, boosting the metabolic sub-volume also resulted in boosting the hypoxic volume, although to a lower dose, but not vice versa.

}, keywords = {Aged, Aged, 80 and over, Carcinoma, Non-Small-Cell Lung, Cell Hypoxia, Female, Humans, Lung Neoplasms, Male, Middle Aged, Positron-Emission Tomography, Radiotherapy Dosage, Radiotherapy Planning, Computer-Assisted}, issn = {1879-0887}, doi = {10.1016/j.radonc.2015.07.013}, author = {Even, Aniek J G and van der Stoep, Judith and Zegers, Catharina M L and Reymen, Bart and Troost, Esther G C and Lambin, Philippe and van Elmpt, Wouter} } @article {56, title = {A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients.}, journal = {Int J Radiat Oncol Biol Phys}, volume = {92}, year = {2015}, month = {2015 Jul 15}, pages = {935-44}, abstract = {

PURPOSE: Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can overcome this but are currently lacking. A DSS for stage III NSCLC requires the development and integration of multiple models. The current study takes the first step in this process by developing and validating a model that can provide physicians with a survival probability for an individual NSCLC patient.

METHODS AND MATERIALS: Data from 548 patients with stage III NSCLC were available to enable the development of a prediction model, using stratified Cox regression. Variables were selected by using a bootstrap procedure. Performance of the model was expressed as the c statistic, assessed internally and on 2 external data sets (n=174 and n=130).

RESULTS: The final multivariate model, stratified for treatment, consisted of age, gender, World Health Organization performance status, overall treatment time, equivalent radiation dose, number of positive lymph node stations, and gross tumor volume. The bootstrapped c statistic was 0.62. The model could identify risk groups in external data sets. Nomograms were constructed to predict an individual patient{\textquoteright}s survival probability (www.predictcancer.org). The data set can be downloaded at https://www.cancerdata.org/10.1016/j.ijrobp.2015.02.048.

CONCLUSIONS: The prediction model for overall survival of patients with stage III NSCLC highlights the importance of combining patient, clinical, and treatment variables. Nomograms were developed and validated. This tool could be used as a first building block for a decision support system.

}, keywords = {Age Factors, Aged, Analysis of Variance, Antineoplastic Combined Chemotherapy Protocols, Carboplatin, Carcinoma, Non-Small-Cell Lung, Chemoradiotherapy, Cisplatin, Deoxycytidine, Etoposide, Female, Gemcitabine, Humans, Lung Neoplasms, Male, Middle Aged, Models, Statistical, Neoplasm Staging, Nomograms, Probability, Radiotherapy Dosage, Regression Analysis, Severity of Illness Index, Sex Factors, Vinblastine, Vinorelbine}, issn = {1879-355X}, doi = {10.1016/j.ijrobp.2015.02.048}, author = {Oberije, Cary and De Ruysscher, Dirk and Houben, Ruud and van de Heuvel, Michel and Uyterlinde, Wilma and Deasy, Joseph O and Belderbos, Jose and Dingemans, Anne-Marie C and Rimner, Andreas and Din, Shaun and Lambin, Philippe} } Error | CancerData.org

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