Research ExplorerPublicationsBayesian Cure Rate Modeling of Local Tumor Control: Evaluati...

Bayesian Cure Rate Modeling of Local Tumor Control: Evaluation in Stereotactic Body Radiation Therapy for Pulmonary Metastases

Standard

Bayesian Cure Rate Modeling of Local Tumor Control: Evaluation in Stereotactic Body Radiation Therapy for Pulmonary Metastases. / Klement, Rainer J; Allgäuer, Michael; Andratschke, Nicolaus; Blanck, Oliver; Boda-Heggemann, Judit; Dieckmann, Karin; Duma, Marciana; Ernst, Iris; Flentje, Michael; Ganswindt, Ute; Hass, Peter; Henkenberens, Christoph; Imhoff, Detlef; Kahl, Henning K; Krempien, Robert; Lohaus, Fabian; Nestle, Ursula; Nevinny-Stickel, Meinhard; Petersen, Cordula; Schmitt, Vanessa; Semrau, Sabine; Sterzing, Florian; Streblow, Jan; Wendt, Thomas G; Wittig, Andrea; Guckenberger, Matthias.

In: INT J RADIAT ONCOL, Vol. 94, No. 4, 15.03.2016, p. 841-9.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Klement, RJ, Allgäuer, M, Andratschke, N, Blanck, O, Boda-Heggemann, J, Dieckmann, K, Duma, M, Ernst, I, Flentje, M, Ganswindt, U, Hass, P, Henkenberens, C, Imhoff, D, Kahl, HK, Krempien, R, Lohaus, F, Nestle, U, Nevinny-Stickel, M, Petersen, C, Schmitt, V, Semrau, S, Sterzing, F, Streblow, J, Wendt, TG, Wittig, A & Guckenberger, M 2016, 'Bayesian Cure Rate Modeling of Local Tumor Control: Evaluation in Stereotactic Body Radiation Therapy for Pulmonary Metastases', INT J RADIAT ONCOL, vol. 94, no. 4, pp. 841-9. https://doi.org/10.1016/j.ijrobp.2015.12.004

APA

Klement, R. J., Allgäuer, M., Andratschke, N., Blanck, O., Boda-Heggemann, J., Dieckmann, K., Duma, M., Ernst, I., Flentje, M., Ganswindt, U., Hass, P., Henkenberens, C., Imhoff, D., Kahl, H. K., Krempien, R., Lohaus, F., Nestle, U., Nevinny-Stickel, M., Petersen, C., ... Guckenberger, M. (2016). Bayesian Cure Rate Modeling of Local Tumor Control: Evaluation in Stereotactic Body Radiation Therapy for Pulmonary Metastases. INT J RADIAT ONCOL, 94(4), 841-9. https://doi.org/10.1016/j.ijrobp.2015.12.004

Vancouver

Klement RJ, Allgäuer M, Andratschke N, Blanck O, Boda-Heggemann J, Dieckmann K et al. Bayesian Cure Rate Modeling of Local Tumor Control: Evaluation in Stereotactic Body Radiation Therapy for Pulmonary Metastases. INT J RADIAT ONCOL. 2016 Mar 15;94(4):841-9. https://doi.org/10.1016/j.ijrobp.2015.12.004

Bibtex

@article{561eecbe9aa64a1c97570c6cec5cf91d,
title = "Bayesian Cure Rate Modeling of Local Tumor Control: Evaluation in Stereotactic Body Radiation Therapy for Pulmonary Metastases",
abstract = "PURPOSE: Most radiobiological models for prediction of tumor control probability (TCP) do not account for the fact that many events could remain unobserved because of censoring. We therefore evaluated a set of TCP models that take into account this censoring.METHODS AND MATERIALS: We applied 2 fundamental Bayesian cure rate models to a sample of 770 pulmonary metastasis treated with stereotactic body radiation therapy at German, Austrian, and Swiss institutions: (1) the model developed by Chen, Ibrahim and Sinha (the CIS99 model); and (2) a mixture model similar to the classic model of Berkson and Gage (the BG model). In the CIS99 model the number of clonogens surviving the radiation treatment follows a Poisson distribution, whereas in the BG model only 1 dominant recurrence-competent tissue mass may remain. The dose delivered to the isocenter, tumor size and location, sex, age, and pretreatment chemotherapy were used as covariates for regression.RESULTS: Mean follow-up time was 15.5 months (range: 0.1-125). Tumor recurrence occurred in 11.6% of the metastases. Delivered dose, female sex, peripheral tumor location and having received no chemotherapy before RT were associated with higher TCP in all models. Parameter estimates of the CIS99 were consistent with the classical Cox proportional hazards model. The dose required to achieve 90% tumor control after 15.5 months was 146 (range: 114-188) Gy10 in the CIS99 and 133 (range: 101-164) Gy10 in the BG model; however, the BG model predicted lower tumor control at long (≳20 months) follow-up times and gave a suboptimal fit to the data compared to the CIS99 model.CONCLUSIONS: Biologically motivated cure rate models allow adding the time component into TCP modeling without being restricted to the follow-up period which is the case for the Cox model. In practice, application of such models to the clinical setting could allow for adaption of treatment doses depending on whether local control should be achieved in the short or longer term.",
keywords = "Adolescent, Adult, Aged, Aged, 80 and over, Bayes Theorem, Child, Databases, Factual, Female, Follow-Up Studies, Humans, Lung Neoplasms, Male, Middle Aged, Models, Biological, Models, Theoretical, Neoplasm Recurrence, Local, Poisson Distribution, Probability, Radiosurgery, Radiotherapy Dosage, Retrospective Studies, Time Factors, Young Adult, Journal Article, Multicenter Study",
author = "Klement, {Rainer J} and Michael Allg{\"a}uer and Nicolaus Andratschke and Oliver Blanck and Judit Boda-Heggemann and Karin Dieckmann and Marciana Duma and Iris Ernst and Michael Flentje and Ute Ganswindt and Peter Hass and Christoph Henkenberens and Detlef Imhoff and Kahl, {Henning K} and Robert Krempien and Fabian Lohaus and Ursula Nestle and Meinhard Nevinny-Stickel and Cordula Petersen and Vanessa Schmitt and Sabine Semrau and Florian Sterzing and Jan Streblow and Wendt, {Thomas G} and Andrea Wittig and Matthias Guckenberger",
note = "Copyright {\textcopyright} 2016 Elsevier Inc. All rights reserved.",
year = "2016",
month = mar,
day = "15",
doi = "10.1016/j.ijrobp.2015.12.004",
language = "English",
volume = "94",
pages = "841--9",
journal = "INT J RADIAT ONCOL",
issn = "0360-3016",
publisher = "Elsevier Inc.",
number = "4",

}

RIS

TY - JOUR

T1 - Bayesian Cure Rate Modeling of Local Tumor Control: Evaluation in Stereotactic Body Radiation Therapy for Pulmonary Metastases

AU - Klement, Rainer J

AU - Allgäuer, Michael

AU - Andratschke, Nicolaus

AU - Blanck, Oliver

AU - Boda-Heggemann, Judit

AU - Dieckmann, Karin

AU - Duma, Marciana

AU - Ernst, Iris

AU - Flentje, Michael

AU - Ganswindt, Ute

AU - Hass, Peter

AU - Henkenberens, Christoph

AU - Imhoff, Detlef

AU - Kahl, Henning K

AU - Krempien, Robert

AU - Lohaus, Fabian

AU - Nestle, Ursula

AU - Nevinny-Stickel, Meinhard

AU - Petersen, Cordula

AU - Schmitt, Vanessa

AU - Semrau, Sabine

AU - Sterzing, Florian

AU - Streblow, Jan

AU - Wendt, Thomas G

AU - Wittig, Andrea

AU - Guckenberger, Matthias

N1 - Copyright © 2016 Elsevier Inc. All rights reserved.

PY - 2016/3/15

Y1 - 2016/3/15

N2 - PURPOSE: Most radiobiological models for prediction of tumor control probability (TCP) do not account for the fact that many events could remain unobserved because of censoring. We therefore evaluated a set of TCP models that take into account this censoring.METHODS AND MATERIALS: We applied 2 fundamental Bayesian cure rate models to a sample of 770 pulmonary metastasis treated with stereotactic body radiation therapy at German, Austrian, and Swiss institutions: (1) the model developed by Chen, Ibrahim and Sinha (the CIS99 model); and (2) a mixture model similar to the classic model of Berkson and Gage (the BG model). In the CIS99 model the number of clonogens surviving the radiation treatment follows a Poisson distribution, whereas in the BG model only 1 dominant recurrence-competent tissue mass may remain. The dose delivered to the isocenter, tumor size and location, sex, age, and pretreatment chemotherapy were used as covariates for regression.RESULTS: Mean follow-up time was 15.5 months (range: 0.1-125). Tumor recurrence occurred in 11.6% of the metastases. Delivered dose, female sex, peripheral tumor location and having received no chemotherapy before RT were associated with higher TCP in all models. Parameter estimates of the CIS99 were consistent with the classical Cox proportional hazards model. The dose required to achieve 90% tumor control after 15.5 months was 146 (range: 114-188) Gy10 in the CIS99 and 133 (range: 101-164) Gy10 in the BG model; however, the BG model predicted lower tumor control at long (≳20 months) follow-up times and gave a suboptimal fit to the data compared to the CIS99 model.CONCLUSIONS: Biologically motivated cure rate models allow adding the time component into TCP modeling without being restricted to the follow-up period which is the case for the Cox model. In practice, application of such models to the clinical setting could allow for adaption of treatment doses depending on whether local control should be achieved in the short or longer term.

AB - PURPOSE: Most radiobiological models for prediction of tumor control probability (TCP) do not account for the fact that many events could remain unobserved because of censoring. We therefore evaluated a set of TCP models that take into account this censoring.METHODS AND MATERIALS: We applied 2 fundamental Bayesian cure rate models to a sample of 770 pulmonary metastasis treated with stereotactic body radiation therapy at German, Austrian, and Swiss institutions: (1) the model developed by Chen, Ibrahim and Sinha (the CIS99 model); and (2) a mixture model similar to the classic model of Berkson and Gage (the BG model). In the CIS99 model the number of clonogens surviving the radiation treatment follows a Poisson distribution, whereas in the BG model only 1 dominant recurrence-competent tissue mass may remain. The dose delivered to the isocenter, tumor size and location, sex, age, and pretreatment chemotherapy were used as covariates for regression.RESULTS: Mean follow-up time was 15.5 months (range: 0.1-125). Tumor recurrence occurred in 11.6% of the metastases. Delivered dose, female sex, peripheral tumor location and having received no chemotherapy before RT were associated with higher TCP in all models. Parameter estimates of the CIS99 were consistent with the classical Cox proportional hazards model. The dose required to achieve 90% tumor control after 15.5 months was 146 (range: 114-188) Gy10 in the CIS99 and 133 (range: 101-164) Gy10 in the BG model; however, the BG model predicted lower tumor control at long (≳20 months) follow-up times and gave a suboptimal fit to the data compared to the CIS99 model.CONCLUSIONS: Biologically motivated cure rate models allow adding the time component into TCP modeling without being restricted to the follow-up period which is the case for the Cox model. In practice, application of such models to the clinical setting could allow for adaption of treatment doses depending on whether local control should be achieved in the short or longer term.

KW - Adolescent

KW - Adult

KW - Aged

KW - Aged, 80 and over

KW - Bayes Theorem

KW - Child

KW - Databases, Factual

KW - Female

KW - Follow-Up Studies

KW - Humans

KW - Lung Neoplasms

KW - Male

KW - Middle Aged

KW - Models, Biological

KW - Models, Theoretical

KW - Neoplasm Recurrence, Local

KW - Poisson Distribution

KW - Probability

KW - Radiosurgery

KW - Radiotherapy Dosage

KW - Retrospective Studies

KW - Time Factors

KW - Young Adult

KW - Journal Article

KW - Multicenter Study

U2 - 10.1016/j.ijrobp.2015.12.004

DO - 10.1016/j.ijrobp.2015.12.004

M3 - SCORING: Journal article

C2 - 26972657

VL - 94

SP - 841

EP - 849

JO - INT J RADIAT ONCOL

JF - INT J RADIAT ONCOL

SN - 0360-3016

IS - 4

ER -