In a groundbreaking series of investigations conducted by University at Buffalo researchers and their collaborators, new light has been shed on the intricate relationship between oral mucositis and infection risks in patients undergoing hematopoietic stem cell transplantation (HSCT) for blood cancers. Oral mucositis, a distressing and painful condition characterized by inflammation and ulceration of the mucous membranes in the mouth, has long been recognized as a significant complication during cancer therapies. However, this recent research has, for the first time, quantified the extent to which oral mucositis heightens susceptibility to severe infections, revealing that affected patients face nearly a fourfold increase in risk compared to those who do not develop the condition.
The study, published on August 14, 2025, in the prestigious journal Cancers, is the most comprehensive synthesis to date, offering an exhaustive meta-analysis that not only confirms the critical infection risk posed by oral mucositis but also delineates specific predisposing factors. Researchers identified a spectrum of variables contributing to increased vulnerability, including the administration of certain chemotherapeutic agents—most notably methotrexate—high-dose chemotherapy regimens, biological sex, age, renal function, and viral factors such as the reactivation of latent herpes simplex virus. This granular delineation of risk factors marks an evolution in understanding, setting a foundation for targeted prevention and intervention.
Oral mucositis, beyond its sheer discomfort and impairment of oral function, acts as a significant biological portal facilitating microbial invasion in immunocompromised hosts. According to Dr. Satheeshkumar Poolakkad Sankaran from UB’s Department of Medicine, the condition dramatically compromises mucosal barriers, thereby increasing infection rates and influencing clinical outcomes negatively. The mucosal breaches serve as entry points for opportunistic pathogens in patients whose immune defenses are already severely impaired by chemotherapy and immunosuppressive therapies integral to HSCT protocols. This systemic linkage underscores the critical need for vigilant risk stratification and proactive management of oral mucositis.
Given the high prevalence of oral mucositis in HSCT recipients—affecting up to 80% of patients—the imperative for preemptive risk screening is apparent. Early identification of patients at elevated risk allows clinicians to implement preventative measures, such as rigorous oral hygiene protocols or cryotherapy, which utilizes localized cooling to mitigate inflammatory responses and mucosal injury. These clinical strategies, informed by precise risk profiling, hold the potential to enhance patient quality of life significantly, reduce morbidity, and shorten hospital stays.
To facilitate individualized risk assessment, the team developed a sophisticated nomogram—a graphical predictive tool that uses variable inputs to estimate a patient’s likelihood of developing ulcerative mucositis, a severe form of the condition. Parameters integrated into this model include demographic data such as age, gender, and race, alongside clinical factors like total body irradiation exposure and the presence of fluid or electrolyte imbalances. Such a tool empowers health care providers with an accessible yet powerful means to forecast mucositis risk and tailor supportive care accordingly.
This predictive innovation was elaborated upon in a prior publication within Supportive Care in Cancer, where the nomogram’s utility in clinical decision-making was thoroughly detailed. The integration of multiple, interdependent patient characteristics into a usable statistical framework represents a significant advancement, translating complex biomedical data into actionable insights. This methodology exemplifies the shift toward precision medicine paradigms in oncology supportive care.
Beyond traditional statistical models, UB researchers are pushing the frontiers of prediction technology by harnessing the capabilities of explainable artificial intelligence (AI). Presented at the Multinational Association of Supportive Care in Cancer meeting in June 2025, the explainable AI model leverages machine learning algorithms to analyze subtle, multi-dimensional patterns in clinical and demographic data that conventional nomograms may overlook. Crucially, this AI framework is designed to elucidate the rationale behind its risk predictions, thus promoting transparency and trust among clinicians.
The enhanced predictive power demonstrated by the AI model delivers nuanced detection of toxicity patterns linked to treatment adverse events, enabling more precise stratification of patient risk profiles. Such capabilities promise to inform therapeutic adjustments personalized to minimize side effects while maintaining treatment efficacy. The fusion of AI with clinical expertise heralds a transformative approach to managing complex oncology care challenges.
Looking forward, Dr. Poolakkad Sankaran and his team are expanding validation efforts of this AI framework to encompass a wider array of cancer-related adverse events, including immune-related toxicities which often arise during novel immunotherapy regimens. Collaborative efforts with experts such as Dr. Roberto Pili are underway to refine and test the model’s applicability across diverse patient populations. This work aspires not merely to academic advancement but to tangible clinical deployment, optimizing patient outcomes on a systemic scale.
The synthesis of these interconnected studies underscores the vital oral-systemic nexus in cancer therapy management, emphasizing the importance of multidisciplinary collaboration. Integrating insights from oncologists, dental specialists, and AI technologists is crucial to fully harness the potential of predictive tools in oncology. Such synergy propels the development of comprehensive treatment strategies that address both disease eradication and complication mitigation.
As the landscape of cancer therapeutics evolves—with HSCT and immunotherapies becoming increasingly prevalent, especially among older and medically complex populations—these innovative predictive models could markedly reduce hospitalization durations, adverse event rates, and overall healthcare costs. The research not only advances scientific understanding but also aligns with the broader goals of value-based care in oncology.
Contributing authors to this impactful work span multiple institutions, reflecting a rich tapestry of expertise. Members hail from the Jacobs School of Medicine and Biomedical Sciences at University at Buffalo, City of Hope Comprehensive Cancer Center, Boston Medical Center, and the University of Connecticut Health Center. This collaborative network epitomizes the integration of academic rigor and clinical acumen.
These efforts are part of the Worldwide Extension of Buffalo’s Research Innovation Group in Hematology/Oncology Talent (WE-BRIGHT) Network, an initiative focused on cultivating emergent leaders in cancer research through mentorship and intensive training. This pipeline supports the sustained progression of innovative, multidisciplinary approaches in cancer care research.
The research was supported in part by the Kaleida Health Foundation, which underscores the vital role of philanthropic and institutional backing in fueling transformative scientific inquiry. Together, these studies chart a promising trajectory toward improving patient experiences and clinical outcomes in complex cancer treatment settings.
Subject of Research: People
Article Title: Elevated Likelihood of Infectious Complications Related to Oral Mucositis After Hematopoietic Stem Cell Transplantation: A Systematic Review and Meta-Analysis of Outcomes and Risk Factors
News Publication Date: 14-Aug-2025
Web References: https://www.mdpi.com/2072-6694/17/16/2657
References: Meta-analysis published in Cancers (DOI: 10.3390/cancers17162657)
Keywords: Cancer, Blood cancer, Cell therapies
