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

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• 作者：Rainer J. Klement ; PhD^&lowast ; ; ^{rainer_klement@gmx.de" class="auth_mail" title="E-mail the corresponding author} ; Michael Allgä ; uer ; MD^&dagger ; ; Nicolaus Andratschke ; MD^&Dagger ; ; ^§ ; ; Oliver Blanck ; PhD^‖ ; Judit Boda-Heggemann ; MD ; PhD^¶ ; ; Karin Dieckmann ; MD^# ; Marciana Duma ; MD^&lowast ; &lowast ; ; Iris Ernst ; MD^&dagger ; &dagger ; ; Michael Flentje ; MD^&Dagger ; &Dagger ; ; Ute Ganswindt ; MD^§ ; § ; ; Peter Hass ; MD^‖‖ ; Christoph Henkenberens ; MD^¶ ; ¶ ; ; Detlef Imhoff ; MD^## ; Henning K. Kahl ; MD^&lowast ; &lowast ; &lowast ; ; Robert Krempien ; MD^&dagger ; &dagger ; &dagger ; ; Fabian Lohaus ; MD^&Dagger ; &Dagger ; &Dagger ; ; Ursula Nestle ; MD^§ ; § ; § ; ; Meinhard Nevinny-Stickel ; MD^‖‖‖ ; Cordula Petersen ; MD^¶ ; ¶ ; ¶ ; ; Vanessa Schmitt ; MD^### ; Sabine Semrau ; MD^&lowast ; &lowast ; &lowast ; &lowast ; ; Florian Sterzing ; MD^&dagger ; &dagger ; &dagger ; &dagger ; ; Jan Streblow ; MD^&dagger ; &dagger ; &dagger ; &dagger ; ; Thomas G. Wendt ; MD^&Dagger ; &Dagger ; &Dagger ; &Dagger ; ; Andrea Wittig ; MD^§ ; § ; § ; § ; ; Matthias Guckenberger ; MD^&Dagger ; ; ^&Dagger ; &Dagger ;
• 刊名：International Journal of Radiation Oncology*Biology*Physics
• 出版年：2016
• 出版时间：15 March 2016
• 年：2016
• 卷：94
• 期：4
• 页码：841-849
• 全文大小：821 K

文摘

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$\mathrm{\gtrsim }20$ 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.