Prognostic potential of mid‐treatment nodal response in oropharyngeal squamous cell carcinoma

Byun, David J.; Tam, Moses; Jacobson, Adam S.; Persky, Mark S.; Tran, T.; Givi, Babak; DeLacure, Mark D.; Li, Zujun; Harrison, Louis B.; Hu, Kenneth

doi:10.1002/hed.26467

Cited by 7 publications

(5 citation statements)

References 28 publications

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“…The survival data for these two strata were compared using the log rank statistical test to test the null hypothesis that there is no difference between the survival curves, and this test yielded a p-value of 0.01. This stratification is in line with the prognostic value of mid-treatment nodal response observed by other groups [19]. The definition of these strata enables the relation of tumor volume changes and estimated personalized RT dose with patient outcomes.…”

Section: Patient Datasupporting

confidence: 72%

Dynamics-Adapted Radiotherapy Dose (DARD) for Head and Neck Cancer Radiotherapy Dose Personalization

Zahid

Mohamed

Caudell

et al. 2021

JPM

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Standard of care radiotherapy (RT) doses have been developed as a one-size-fits all approach designed to maximize tumor control rates across a population. Although this has led to high control rates for head and neck cancer with 66–70 Gy, this is done without considering patient heterogeneity. We present a framework to estimate a personalized RT dose for individual patients, based on pre- and early on-treatment tumor volume dynamics—a dynamics-adapted radiotherapy dose (DDARD). We also present the results of an in silico trial of this dose personalization using retrospective data from a combined cohort of n = 39 head and neck cancer patients from the Moffitt and MD Anderson Cancer Centers that received 66–70 Gy RT in 2–2.12 Gy weekday fractions. This trial was repeated constraining DDARD between (54, 82) Gy to test more moderate dose adjustment. DDARD was estimated to range from 8 to 186 Gy, and our in silico trial estimated that 77% of patients treated with standard of care were overdosed by an average dose of 39 Gy, and 23% underdosed by an average dose of 32 Gy. The in silico trial with constrained dose adjustment estimated that locoregional control could be improved by >10%. We demonstrated the feasibility of using early treatment tumor volume dynamics to inform dose personalization and stratification for dose escalation and de-escalation. These results demonstrate the potential to both de-escalate most patients, while still improving population-level control rates.

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Section: Patient Datasupporting

confidence: 72%

Dynamics-Adapted Radiotherapy Dose (DARD) for Head and Neck Cancer Radiotherapy Dose Personalization

Zahid

Mohamed

Caudell

et al. 2021

JPM

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“…In head and neck cancer, mid-treatment volumetric responses correlate with outcome ( 31 , 47 ). Patients with greater than 32.2% tumor volume reduction after 4 weeks of RT were 100% locoregionally controlled (LRC) at a mean follow-up time of 20 months.…”

Section: Methodsmentioning

confidence: 99%

Mathematical modeling of radiotherapy: impact of model selection on estimating minimum radiation dose for tumor control

Kutuva,

Caudell,

Yamoah

et al. 2023

Front. Oncol.

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IntroductionRadiation therapy (RT) is one of the most common anticancer therapies. Yet, current radiation oncology practice does not adapt RT dose for individual patients, despite wide interpatient variability in radiosensitivity and accompanying treatment response. We have previously shown that mechanistic mathematical modeling of tumor volume dynamics can simulate volumetric response to RT for individual patients and estimation personalized RT dose for optimal tumor volume reduction. However, understanding the implications of the choice of the underlying RT response model is critical when calculating personalized RT dose.MethodsIn this study, we evaluate the mathematical implications and biological effects of 2 models of RT response on dose personalization: (1) cytotoxicity to cancer cells that lead to direct tumor volume reduction (DVR) and (2) radiation responses to the tumor microenvironment that lead to tumor carrying capacity reduction (CCR) and subsequent tumor shrinkage. Tumor growth was simulated as logistic growth with pre-treatment dynamics being described in the proliferation saturation index (PSI). The effect of RT was simulated according to each respective model for a standard schedule of fractionated RT with 2 Gy weekday fractions. Parameter sweeps were evaluated for the intrinsic tumor growth rate and the radiosensitivity parameter for both models to observe the qualitative impact of each model parameter. We then calculated the minimum RT dose required for locoregional tumor control (LRC) across all combinations of the full range of radiosensitvity and proliferation saturation values. ResultsBoth models estimate that patients with higher radiosensitivity will require a lower RT dose to achieve LRC. However, the two models make opposite estimates on the impact of PSI on the minimum RT dose for LRC: the DVR model estimates that tumors with higher PSI values will require a higher RT dose to achieve LRC, while the CCR model estimates that higher PSI values will require a lower RT dose to achieve LRC.DiscussionUltimately, these results show the importance of understanding which model best describes tumor growth and treatment response in a particular setting, before using any such model to make estimates for personalized treatment recommendations.

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“…A study from New York University showed that patients who had low-risk OPC with ≥43% nodal decrease on cone-beam CT by treatment day 20 had superior 2-year LRC. 130 Consequently, in their trial (ClinicalTrials.gov identifier NCT03215719; Table 9), interval scans at 4 weeks will be the in-silico trial of dynamics-adapted dose personalization estimated that 77% of patients treated with SOC 66-70 Gy were overdosed by an average of 39 Gy. 133 Even further beyond this mathematical model predicting that a majority of patients may only need approximately 30 Gy was the most drastic dose de-escalation trial to date, which delivered 30 Gy to the majority of patients: the 30 ROC trial from Memorial Sloan Kettering Cancer Center.…”

Section: Radiomics and Functional Imagingmentioning

confidence: 99%

“…Another approach harnesses radiomics using intratreatment imaging to identify early responders. A study from New York University showed that patients who had low‐risk OPC with ≥43% nodal decrease on cone‐beam CT by treatment day 20 had superior 2‐year LRC 130 . Consequently, in their trial (ClinicalTrials.gov identifier NCT03215719; Table 9), interval scans at 4 weeks will be used to identify responders and adaptively de‐escalate to 60 Gy in patients who have >40% nodal shrinkage.…”

Section: The Future Of De‐escalation: Intratreatment Response Assessm...mentioning

confidence: 99%

Consensuses, controversies, and future directions in treatment deintensification for human papillomavirus‐associated oropharyngeal cancer

Kang

Chen

et al. 2022

CA A Cancer J Clinicians

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The most common cancer caused by human papillomavirus (HPV) infection in the United States is oropharyngeal cancer (OPC), and its incidence has been rising since the turn of the century. Because of substantial long‐term morbidities with chemoradiation and the favorable prognosis of HPV‐positive OPC, identifying the optimal deintensification strategy for this group has been a keystone of academic head‐and‐neck surgery, radiation oncology, and medical oncology for over the past decade. However, the first generation of randomized chemotherapy deintensification trials failed to change the standard of care, triggering concern over the feasibility of de‐escalation. National database studies estimate that up to one third of patients receive nonstandard de‐escalated treatments, which have subspecialty‐specific nuances. A synthesis of the multidisciplinary deintensification data and current treatment standards is important for the oncology community to reinforce best practices and ensure optimal patient outcomes. In this review, the authors present a summary and comparison of prospective HPV‐positive OPC de‐escalation trials. Chemotherapy attenuation compromises outcomes without reducing toxicity. Limited data comparing transoral robotic surgery (TORS) with radiation raise concern over toxicity and outcomes with TORS. There are promising data to support de‐escalating adjuvant therapy after TORS, but consensus on treatment indications is needed. Encouraging radiation deintensification strategies have been reported (upfront dose reduction and induction chemotherapy‐based patient selection), but level I evidence is years away. Ultimately, stage and HPV status may be insufficient to guide de‐escalation. The future of deintensification may lie in incorporating intratreatment response assessments to harness the powers of personalized medicine and integrate real‐time surveillance.

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Prognostic potential of mid‐treatment nodal response in oropharyngeal squamous cell carcinoma

Cited by 7 publications

References 28 publications

Dynamics-Adapted Radiotherapy Dose (DARD) for Head and Neck Cancer Radiotherapy Dose Personalization

Dynamics-Adapted Radiotherapy Dose (DARD) for Head and Neck Cancer Radiotherapy Dose Personalization

Mathematical modeling of radiotherapy: impact of model selection on estimating minimum radiation dose for tumor control

Consensuses, controversies, and future directions in treatment deintensification for human papillomavirus‐associated oropharyngeal cancer

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