Comments on “Challenges in the Future of Cancer Screening”

We read with great interest the recent review article by Lynge et al., titled “Challenges in the future of cancer screening” about the future landscape of cancer screening 1. The authors have astutely identified a paradigm shift away from “one-size-fits-all” population screening towards a personalized, risk-stratified model powered by artificial intelligence (AI). The discussion is aptly focused on optimization of resource allocation especially in financially constrained public health systems. However, we wish to point out a critical omission in this strategic planning methodology which is the exclusion of oral cancer/oral squamous cell carcinoma (OSCC). The review's focus has been on internal malignancies: breast, lung, and colorectal cancer but oral cancer constitutes a unique epidemiological case with the rising prevalence of the disease and appropriately aligns with the authors'. While the review appropriately focuses on major internal malignancies (breast, lung, colorectal), oral cancer represents a unique epidemiological and technological test case that perfectly aligns with the authors' proactive approach. We offer our viewpoints why it is essential to include oral cancer in this global framework: The authors correctly suggest that cancer screening programs must be adapted to include demographic changes. Unlike the stabilization/decrease seen in some screenable cancers, there has been a rising trend in the global burden of oral cancer, especially in low- and middle-income countries which bear this heavy oral cancer burden 2. Most concerningly, we are currently witnessing a significant epidemiological shift: an increasing incidence of OSCC in younger adults (< 40 years) who have conventionally fallen outside the oral cancer screening criteria 3. This particular cohort often lacks the traditional risk factors (tobacco or alcohol), requiring the exact type of “time-dependent predictive frameworks” that Lynge et al. have advocated. Our failure in addressing this escalating pattern will risk a younger, productive cohort being diagnosed at advanced stages. The authors have expressed concern about new screening tools to be acceptable for all responsible health care providers while not being overtly resource demanding. Oral cancer screening offers an accurate solution to this challenge. Unlike the internal cancers that require expensive apparatus (Computed Tomography/mammography), the oral cavity is directly accessible for clinical examination. Recent published data from meta-analyses have shown that AI-driven mobile health (mHealth) tools could achieve specificity and sensitivity of more than 90% in early diagnosis of oral potentially malignant disorders (OPMDs) and OSCC 4, 5. These AI-based tools facilitate “task-shifting,” allowing primary health providers to triage high-risk lesions in public health settings effectively. This aligns with the authors' appeal for AI-based innovations that lessen the specialist/oncologist workload while cutting costs. This review emphasizes moving towards risk-stratified screening to minimize overdiagnosis. Oral oncology is probably the most apt field for this diagnostic approach. We possess actionable, well-defined risk factors like tobacco, arecanut, alcohol, HPV, and so forth, allowing precise population stratification as summarized in Table 1 7. Integration of such behavioral markers in screening algorithms would result in the formation of one of the most cost-effective interventions in oncology, especially in high-prevalence regions like the Indian subcontinent/South Asia where “high-risk” targeted opportunistic screening has already proven more economical than mass screening 6. To conclude, the future of cancer screening as described by the authors is one which is defined by AI, risk stratification with resource optimization, and has already arrived in oral oncology settings. The international community must broaden the cancer screening priorities to include oral malignancies, especially OSCC. Doing this will take care of a rising global burden while providing a successful model for a low-resource, high-tech screening tool. Satya Ranjan Misra: conceptualization, writing – review and editing, writing – original draft, visualization. Rupsa Das: supervision, validation. The authors declare no conflicts of interest.