RadioBio data: A Moddicom Module to Predict Tumor Control Probability and Normal Tissue Complication Probability in Radiotherapy

Background/Aim: The aim of the study was to evaluate acute and late genitourinary (GU) and gastrointestinal (GI) toxicity in patients with high-or intermediate-risk prostate cancer. Patients and Methods: We evaluated data of patients from three Radiation Oncology Departments (Rome, Lübeck and Perugia). Patients treated in Rome underwent exclusive intensity-modulatedradiotherapy (IMRT) or IMRT plus high-dose-rate interventional radiotherapy (HDR-IRT). IMRT plus two fractions HDR-IRT was performed in Lübeck, while in Perugia Helical Tomotherapy was performed. The Common Toxicity Criteria for Adverse Event (Version 4.03) scale was used to describe acute and late toxicity. Results: At a median follow-up of 28 months, all 51 patients were alive and disease-free. Patients treated by HDR-IRT plus VMAT showed only G1-2 genitourinary-gastrointestinal (GU-GI) acute and late toxicity. Univariate analysis showed a lower risk of acute GU toxicity (p=0.048) in IMRT+HDR-IRT. Conclusion: Low grade and less acute GU toxicity was observed in patients undergoing HDR-IRT boost.

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“…Many studies focused on the possibility of using predictive models not only for clinical outcomes, but also for toxicity occurrence (50,51).…”

Section: Discussionmentioning

confidence: 99%

BIT-ART: Multicentric Comparison of HDR-brachytherapy, Intensity-modulated Radiotherapy and Tomotherapy for Advanced Radiotherapy in Prostate Cancer

Alitto

Tagliaferri

Lancellotta

et al. 2020

In Vivo

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“…A small sample of 123 prostate cancer patients was used only to validate our methodology and our developed software [29]: DSSs elaboration will need a bigger sample, even from multiple centres.…”

Section: Discussionmentioning

confidence: 99%

“…In particular, our methodology and tools have been verified on a small sample of 123 prostate cancer patients, to provide a validation of our software, that we will use for our next analysis on a big sample [29] to elaborate DSSs. We focused our tests on developing techniques and methodologies to train DSS in multi-centric environment ensuring patient's privacy, without exchanging patient's data [18].…”

Section: Variable Identification and Representationmentioning

confidence: 99%

PRODIGE: Prediction Models in Prostate Cancer for Personalized Medicine Challenge

et al. 2017

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“…Data were analyzed by using R statistical software version 3.3.1 and by the in-house developed software package “Moddicom” [ 13 , 23 ]. A p -value cutoff of 0.05 was considered for significance.…”

Section: Methodsmentioning

confidence: 99%

“…Identifying new indicators and developing models that could predict toxicity is important to choose the best treatment for patients [ 10 , 11 , 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

Predicting Radiotherapy Impact on Late Bladder Toxicity in Prostate Cancer Patients: An Observational Study

Catucci

Alitto

Masciocchi

et al. 2021

Cancers

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Background and purpose: The aim of our study was to elaborate a suitable model on bladder late toxicity in prostate cancer (PC) patients treated by radiotherapy with volumetric technique. Materials and methods: PC patients treated between September 2010 and April 2017 were included in the analysis. An observational study was performed collecting late toxicity data of any grade, according to RTOG and CTCAE 4.03 scales, cumulative dose volumes histograms were exported for each patient. Vdose, the value of dose to a specific volume of organ at risk (OAR), impact was analyzed through the Mann–Whitney rank-sum test. Logistic regression was used as the final model. The model performance was estimated by taking 1000 samples with replacement from the original dataset and calculating the AUC average. In addition, the calibration plot (Hosmer–Lemeshow goodness-of-fit test) was used to evaluate the performance of internal validation. RStudio Software version 3.3.1 and an in house developed software package “Moddicom” were used. Results: Data from 175 patients were collected. The median follow-up was 39 months (min–max 3.00–113.00). We performed Mann–Whitney rank-sum test with continuity correction in the subset of patients with late bladder toxicity grade ≥ 2: a statistically significant p-value with a Vdose of 51.43 Gy by applying a logistic regression model (coefficient 4.3, p value 0.025) for the prediction of the development of late G ≥ 2 GU toxicity was observed. The performance for the model’s internal validation was evaluated, with an AUC equal to 0.626. Accuracy was estimated through the elaboration of a calibration plot. Conclusions: Our preliminary results could help to optimize treatment planning procedures and customize treatments.

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RadioBio data: A Moddicom Module to Predict Tumor Control Probability and Normal Tissue Complication Probability in Radiotherapy

Cited by 5 publications

References 16 publications

BIT-ART: Multicentric Comparison of HDR-brachytherapy, Intensity-modulated Radiotherapy and Tomotherapy for Advanced Radiotherapy in Prostate Cancer

BIT-ART: Multicentric Comparison of HDR-brachytherapy, Intensity-modulated Radiotherapy and Tomotherapy for Advanced Radiotherapy in Prostate Cancer

PRODIGE: Prediction Models in Prostate Cancer for Personalized Medicine Challenge

Predicting Radiotherapy Impact on Late Bladder Toxicity in Prostate Cancer Patients: An Observational Study

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