BACKGROUND: A mathematical framework is presented for simultaneously quantifying and evaluating the trade-off between tumor control and late complications for risk-based radiation therapy (RT) decision-support. To demonstrate this, we estimate life years lost (LYL) attributable to tumor recurrence, late cardiac toxicity and secondary cancers for standard-risk pediatric medulloblastoma (MB) patients and compare the effect of dose re-distribution on a common scale. METHODS: Total LYL were derived, based on the LYL attributable to radiation-induced late complications and the LYL from not controlling the primary disease. We compared the estimated LYL for three different treatments in 10 patients: 1) standard 3D conformal RT; 2) proton therapy; 3) risk-adaptive photon treatment lowering the dose to part of the craniospinal (CS) target volume situated close to critical risk organs. RESULTS: Late toxicity is important, with 0.75 LYL (95% CI 0.60-7.2 years) for standard uniform 24 Gy CS irradiation. However, recurrence risk dominates the total LYL with 14.2 years (95% CI 13.4-16.6 years). Compared to standard treatment, a risk-adapted strategy prescribing 12 Gy to the spinal volume encompassing the 1st-10th thoracic vertebrae (Th1-Th10), and 36 Gy to the remaining CS volume, estimated a LYL reduction of 0.90 years (95% CI -0.18-2.41 years). Proton therapy with 36 Gy to the whole CS volume was associated with significantly fewer LYL compared to the risk-adapted photon strategies, with a mean LYL difference of 0.50 years (95% CI 0.25-2.60 years). CONCLUSIONS: Optimization of RT prescription strategies considering both late complications and the risk of recurrence, an all-cause mortality dose painting approach, was demonstrated. The risk-adapted techniques compared favorably to the standard, and although in this context, the gain is small compared to estimated uncertainty, this study demonstrates a framework for all-cause mortality risk estimation, rather than evaluates direct clinical applicability of risk-adapted strategies.
BACKGROUND: A mathematical framework is presented for simultaneously quantifying and evaluating the trade-off between tumor control and late complications for risk-based radiation therapy (RT) decision-support. To demonstrate this, we estimate life years lost (LYL) attributable to tumor recurrence, late cardiac toxicity and secondary cancers for standard-risk pediatric medulloblastoma (MB) patients and compare the effect of dose re-distribution on a common scale. METHODS: Total LYL were derived, based on the LYL attributable to radiation-induced late complications and the LYL from not controlling the primary disease. We compared the estimated LYL for three different treatments in 10 patients: 1) standard 3D conformal RT; 2) proton therapy; 3) risk-adaptive photon treatment lowering the dose to part of the craniospinal (CS) target volume situated close to critical risk organs. RESULTS: Late toxicity is important, with 0.75 LYL (95% CI 0.60-7.2 years) for standard uniform 24 Gy CS irradiation. However, recurrence risk dominates the total LYL with 14.2 years (95% CI 13.4-16.6 years). Compared to standard treatment, a risk-adapted strategy prescribing 12 Gy to the spinal volume encompassing the 1st-10th thoracic vertebrae (Th1-Th10), and 36 Gy to the remaining CS volume, estimated a LYL reduction of 0.90 years (95% CI -0.18-2.41 years). Proton therapy with 36 Gy to the whole CS volume was associated with significantly fewer LYL compared to the risk-adapted photon strategies, with a mean LYL difference of 0.50 years (95% CI 0.25-2.60 years). CONCLUSIONS: Optimization of RT prescription strategies considering both late complications and the risk of recurrence, an all-cause mortality dose painting approach, was demonstrated. The risk-adapted techniques compared favorably to the standard, and although in this context, the gain is small compared to estimated uncertainty, this study demonstrates a framework for all-cause mortality risk estimation, rather than evaluates direct clinical applicability of risk-adapted strategies.
Authors: J S Kornerup; N P Brodin; T Björk-Eriksson; C Birk Christensen; A Kiil-Berthelsen; M C Aznar; C Hollensen; E Markova; P Munck Af Rosenschöld Journal: Br J Radiol Date: 2014-12-12 Impact factor: 3.039
Authors: Laura A Rechner; John G Eley; Rebecca M Howell; Rui Zhang; Dragan Mirkovic; Wayne D Newhauser Journal: Phys Med Biol Date: 2015-04-28 Impact factor: 3.609
Authors: Clemens Grassberger; Daniel Shinnick; Beow Y Yeap; Mark Tracy; Susannah G Ellsworth; Clayton B Hess; Elizabeth A Weyman; Sara L Gallotto; Miranda P Lawell; Benjamin Bajaj; David H Ebb; Myrsini Ioakeim-Ioannidou; Jay S Loeffler; Shannon M MacDonald; Nancy J Tarbell; Torunn I Yock Journal: Int J Radiat Oncol Biol Phys Date: 2021-02-05 Impact factor: 8.013
Authors: Wayne D Newhauser; Rui Zhang; Timothy G Jones; Annelise Giebeler; Phillip J Taddei; Robert D Stewart; Andrew Lee; Oleg Vassiliev Journal: Cancers (Basel) Date: 2015-04-24 Impact factor: 6.639