Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence
PurposeFor patients receiving lung stereotactic ablative radiotherapy (SABR), evidence suggests that high peritumor density predicts an increased risk of microscopic disease (MDE) and local-regional failure, but only if there is low or heterogenous incidental dose surrounding the tumor (GTV). A data...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-07-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2023.1156389/full |
| _version_ | 1797782128278110208 |
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| author | Angela Davey Maria Thor Marcel van Herk Corinne Faivre-Finn Corinne Faivre-Finn Andreas Rimner Joseph O. Deasy Alan McWilliam |
| author_facet | Angela Davey Maria Thor Marcel van Herk Corinne Faivre-Finn Corinne Faivre-Finn Andreas Rimner Joseph O. Deasy Alan McWilliam |
| author_sort | Angela Davey |
| collection | DOAJ |
| description | PurposeFor patients receiving lung stereotactic ablative radiotherapy (SABR), evidence suggests that high peritumor density predicts an increased risk of microscopic disease (MDE) and local-regional failure, but only if there is low or heterogenous incidental dose surrounding the tumor (GTV). A data-mining method (Cox-per-radius) has been developed to investigate this dose-density interaction. We apply the method to predict local relapse (LR) and regional failure (RF) in patients with non-small cell lung cancer.Methods199 patients treated in a routine setting were collated from a single institution for training, and 76 patients from an external institution for validation. Three density metrics (mean, 90th percentile, standard deviation (SD)) were studied in 1mm annuli between 0.5cm inside and 2cm outside the GTV boundary. Dose SD and fraction of volume receiving less than 30Gy were studied in annuli 0.5-2cm outside the GTV to describe incidental MDE dosage. Heat-maps were created that correlate with changes in LR and RF rates due to the interaction between dose heterogeneity and density at each distance combination. Regions of significant improvement were studied in Cox proportional hazards models, and explored with and without re-fitting in external data. Correlations between the dose component of the interaction and common dose metrics were reported.ResultsLocal relapse occurred at a rate of 6.5% in the training cohort, and 18% in the validation cohort, which included larger and more centrally located tumors. High peritumor density in combination with high dose variability (0.5 - 1.6cm) predicts LR. No interactions predicted RF. The LR interaction improved the predictive ability compared to using clinical variables alone (optimism-adjusted C-index; 0.82 vs 0.76). Re-fitting model coefficients in external data confirmed the importance of this interaction (C-index; 0.86 vs 0.76). Dose variability in the 0.5-1.6 cm annular region strongly correlates with heterogeneity inside the target volume (SD; ρ = 0.53 training, ρ = 0.65 validation).ConclusionIn these real-world cohorts, the combination of relatively high peritumor density and high dose variability predicts increase in LR, but not RF, following lung SABR. This external validation justifies potential use of the model to increase low-dose CTV margins for high-risk patients. |
| first_indexed | 2024-03-13T00:06:39Z |
| format | Article |
| id | doaj.art-4544f5495b2f4e659db31c742b2211c5 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-03-13T00:06:39Z |
| publishDate | 2023-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-4544f5495b2f4e659db31c742b2211c52023-07-12T23:33:10ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2023-07-011310.3389/fonc.2023.11563891156389Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidenceAngela Davey0Maria Thor1Marcel van Herk2Corinne Faivre-Finn3Corinne Faivre-Finn4Andreas Rimner5Joseph O. Deasy6Alan McWilliam7Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United KingdomDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United StatesDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United KingdomDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United KingdomDepartment of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, United KingdomDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United StatesDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United StatesDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United KingdomPurposeFor patients receiving lung stereotactic ablative radiotherapy (SABR), evidence suggests that high peritumor density predicts an increased risk of microscopic disease (MDE) and local-regional failure, but only if there is low or heterogenous incidental dose surrounding the tumor (GTV). A data-mining method (Cox-per-radius) has been developed to investigate this dose-density interaction. We apply the method to predict local relapse (LR) and regional failure (RF) in patients with non-small cell lung cancer.Methods199 patients treated in a routine setting were collated from a single institution for training, and 76 patients from an external institution for validation. Three density metrics (mean, 90th percentile, standard deviation (SD)) were studied in 1mm annuli between 0.5cm inside and 2cm outside the GTV boundary. Dose SD and fraction of volume receiving less than 30Gy were studied in annuli 0.5-2cm outside the GTV to describe incidental MDE dosage. Heat-maps were created that correlate with changes in LR and RF rates due to the interaction between dose heterogeneity and density at each distance combination. Regions of significant improvement were studied in Cox proportional hazards models, and explored with and without re-fitting in external data. Correlations between the dose component of the interaction and common dose metrics were reported.ResultsLocal relapse occurred at a rate of 6.5% in the training cohort, and 18% in the validation cohort, which included larger and more centrally located tumors. High peritumor density in combination with high dose variability (0.5 - 1.6cm) predicts LR. No interactions predicted RF. The LR interaction improved the predictive ability compared to using clinical variables alone (optimism-adjusted C-index; 0.82 vs 0.76). Re-fitting model coefficients in external data confirmed the importance of this interaction (C-index; 0.86 vs 0.76). Dose variability in the 0.5-1.6 cm annular region strongly correlates with heterogeneity inside the target volume (SD; ρ = 0.53 training, ρ = 0.65 validation).ConclusionIn these real-world cohorts, the combination of relatively high peritumor density and high dose variability predicts increase in LR, but not RF, following lung SABR. This external validation justifies potential use of the model to increase low-dose CTV margins for high-risk patients.https://www.frontiersin.org/articles/10.3389/fonc.2023.1156389/fullimage-based data miningreal world databiomarker-by-treatment interactionslocal relapseNSCLCstereotactic ablative body radiotherapy (SABR) |
| spellingShingle | Angela Davey Maria Thor Marcel van Herk Corinne Faivre-Finn Corinne Faivre-Finn Andreas Rimner Joseph O. Deasy Alan McWilliam Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence Frontiers in Oncology image-based data mining real world data biomarker-by-treatment interactions local relapse NSCLC stereotactic ablative body radiotherapy (SABR) |
| title | Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence |
| title_full | Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence |
| title_fullStr | Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence |
| title_full_unstemmed | Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence |
| title_short | Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence |
| title_sort | predicting cancer relapse following lung stereotactic radiotherapy an external validation study using real world evidence |
| topic | image-based data mining real world data biomarker-by-treatment interactions local relapse NSCLC stereotactic ablative body radiotherapy (SABR) |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2023.1156389/full |
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