Imaging Biomarker May Help to Risk-Stratify Patients With Head and Neck Cancer

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A team of scientists has used artificial intelligence (AI) to identify which patients with certain head and neck cancers may benefit from reducing the intensity of treatments such as radiation therapy and chemotherapy. Their findings were published by Corredor et al in the Journal of the National Cancer Institute.

The researchers used AI tools to analyze digitized images of tissue samples that had been taken from 439 patients with human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma from six hospital systems. The computer program successfully identified a subset of patients who might have benefitted from a significantly reduced dose of radiation therapy.

While the analysis was retrospective, the researchers said their next step could be to test its accuracy in clinical trials.


Researchers clarified that the system was able to accurately define the “spatial arrangement, or architecture, of [tumor-infiltrating] lymphocytes surrounding the cancer cells.” They called the biomarker OP-TIL.

OP-TIL separated patients with stage I HPV-associated oropharyngeal squamous cell carcinoma with 30 or less pack-year smoking history into low-risk (2-year disease-free survival = 94.2%; 5-year disease-free survival = 88.4%) and high-risk (2-year disease-free survival = 82.5%; 5-year disease-free survival = 74.2%) groups (hazard ratio [HR] = 2.56, 95% confidence interval [CI] = 1.52–4.32, P < .001), even after adjusting for age, smoking status, T and N classification, and treatment modality on multivariate analysis for disease-free survival (HR = 2.27, 95% CI = 1.32–3.94, P = .003).

The study authors concluded, “Following validation on previously completed multi-institutional clinical trials, OP-TIL has the potential to be a biomarker, beyond clinical stage and HPV status, that can be used clinically to optimize patient selection for de-escalation.”

Issue of Overtreatment

Although most others with HPV-driven cancer may still benefit from aggressive treatment—along with patients whose cancer was unrelated to the virus—the researchers said their study revealed a significant group was receiving more aggressive therapy than they needed to achieve a favorable outcome.

Clinicians are not able to easily make that distinction simply from simply looking at the tissue scans, the researchers said. So virtually all patients with these cancers—regardless of whether they are HPV-driven or not—are treated with a full course of chemotherapy and radiation.

 “We have been overtreating many patients with chemotherapy and radiation that they do not need because we didn’t have a way to find out which patients would benefit from de-escalation,” said corresponding and senior study author Anat Madabhushi, PhD, said. “We’re saying that now we do—and that someday physicians could modulate the way we care for people and not just give the standard high dose of radiation to everyone who comes through the door.”

Dr. Madabhushi, Director of the Center for Computational Imaging & Personalized Diagnostics (CCIPD) at Case Western Reserve University and the Donnell Institute Professor of Biomedical Engineering at the Case School of Engineering, added that reducing radiation for these patients could also help lessen the “toxicity of radiation therapy,” meaning that they could experience fewer side effects such as dry mouth, swallowing dysfunction, and taste changes.

“There are already national clinical trials ongoing investigating the reduction of radiation therapy and chemotherapy intensity in [patients with] favorable HPV-positive oropharyngeal cancer,” said Shlomo Koyfman, MD, Director of Head and Neck and Skin Cancer Radiation at Cleveland Clinic and a study collaborator. “However, properly selecting the ideal patients for this treatment reduction has been a challenge. This imaging classifier can help us better select patients for these novel treatment paradigms.”

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The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.