Clemson Researcher Sheds Light on Simplified Lung Cancer Screening That Could Save Millions‎‎

By Tosin Clegg

As Lung cancer remains the leading cause of cancer deaths in the United States, claiming over 150,000 lives annually.

However, a new study led by Dr. Marvin Okon, a physician and public health researcher at Clemson University, is offering new hope by simplifying the identification of eligible individuals for lung cancer screening.
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‎In a country where lung cancer screening rates hover below 20 percent, Dr. Okon and his research team developed an approach that could help reach millions of undiagnosed Americans.
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‎The study, published in Translational Cancer Research, analyzed national health data and proposed simplified criteria that facilitate the identification of at-risk populations more easily and efficiently.
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‎According to the research, approximately 16.7 million Americans aged 50 to 80 years meet the current guidelines for lung cancer screening. Yet, many remain undiagnosed due to the difficulty of assessing lifetime smoking intensity, a key factor in determining eligibility.
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‎Dr. Okon’s team discovered that individuals most likely to qualify for lung cancer screening tend to have less favorable socioeconomic and health profiles. These include people who are younger, male, non-Hispanic White, uninsured, or less educated. The study’s findings reveal a deep social imbalance that could worsen existing disparities in healthcare access.
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‎“By understanding who qualifies and simplifying the process, we can close the gap and ensure equitable access to life-saving screening,” said Dr. Okon. His work emphasizes that early detection through low-dose computed tomography (LDCT) can reduce lung cancer mortality by up to 20 percent.
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‎The research evaluated five simplified screening criteria, ranging from identifying anyone who has ever smoked to focusing on those currently smoking over one pack per day.
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‎Remarkably, most of these simplified methods showed strong sensitivity and accuracy, with results ranging from 70 to 91 percent in correctly identifying eligible individuals.
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‎This simplified framework could be a game-changer for public health systems struggling to reach high-risk populations. By using readily available data, such as age and smoking status, healthcare providers can identify potential candidates for screening before conducting more detailed assessments. This framework was designed for adoption by smaller healthcare screening centers or programs with limited resources, where these criteria are incorporated into Electronic Health Records (EHRs) and alerts are generated during pre-screening phases to easily identify eligible lung cancer screening patients.
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‎For Dr. Okon, the study is not just about statistics; it’s about saving lives and improving access to care by utilizing readily available information. As a medical doctor with training from Obafemi Awolowo University in Nigeria and advanced research degrees from Clemson University, his work bridges clinical experience and population-level analysis.
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‎Beyond lung cancer research, Dr. Okon’s portfolio reflects a deep commitment to tackling health disparities. His previous studies on stroke, mental health, maternal obesity, and healthcare access have been published in high-impact journals, including Journal of Stroke and Cerebrovascular Diseases, Translational Cancer Research and the Journal of the American College of Obstetricians and Gynecologists, among others, which have strengthened his reputation as a voice for evidence-based equity in medicine.
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‎Further findings showed that his teaching and analytical work, utilizing advanced statistical tools such as R, SAS, Python, Tableau, and ArcGIS for spatial and place-based health disparities, have made him a key contributor to public health data science.
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‎Dr. Okon’s research reflects a global perspective shaped by his clinical experience in Nigeria, where he served at reputable medical institutions, including Adeoyo Specialist Hospital, Delight Hospital and Fertility Center, and the University College Hospital Ibadan.
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‎ His transition from clinical practice to advanced research underscores his passion for translating data into actionable public health improvements.