Association of low adherence to weekly cisplatin with outcomes in patients with head and neck squamous cell carcinoma: a retrospective cohort study.

BACKGROUND: The National Comprehensive Cancer Network (NCCN) guideline recommends consideration of weekly cisplatin as an alternative option for patients with head and neck cancer undergoing definitive chemoradiation. However, in a recent phase III trial (ConCERT), 20% of patients treated with weekly cisplatin could not receive a total of 200 mg/m2, and the association of low adherence to weekly cisplatin and cancer control outcomes remains unclear. To fill this knowledge gap, we performed an observational cohort study of patients with head and neck cancer undergoing definitive chemoradiation with weekly cisplatin. METHODS: Our institutional database was queried for patients with non-metastatic head and neck cancer who underwent definitive chemoradiation with weekly cisplatin (40 mg/m2) between November 2007 and April 2023. Adherence to weekly cisplatin was defined as receiving at least 5 cycles with a total cumulative dose of 200 mg/m2. Survival outcomes were evaluated using Kaplan-Meier method, log-rank tests, Cox proportional hazard multivariable (MVA) analyses. Logistic MVA was performed to identify variables associated with low adherence to weekly cisplatin. Fine-Gray MVA was performed to analyze failure outcomes with death as a competing event. RESULTS: Among 119 patients who met our criteria, 51 patients (42.9%) had low adherence to weekly cisplatin. Median follow up was 19.8 months (interquartile range 8.8-65.6). Low adherence to weekly cisplatin was associated with worse overall survival (adjusted hazards ratio [aHR] 2.94, 95% confidence interval [CI] 1.58-5.47, p < 0.001) and progression-free survival (aHR 2.32, 95% CI 1.29-4.17, p = 0.005). It was also associated with worse distant failure (aHR 4.55, 95% CI 1.19-17.3, p = 0.03), but not locoregional failure (aHR 1.61, 95% CI 0.46-5.58, p = 0.46). KPS < 90 was the only variable associated with low adherence to weekly cisplatin (adjusted odds ratio [aOR] 2.67, 95% CI 1.10-6.65, p = 0.03). CONCLUSION: Our study suggested that over 40% of patients underwent fewer than 5 weekly cisplatin cycles and that low adherence to weekly cisplatin was an independent, adverse prognostic factor for worse survival and distant failure outcomes. Those with reduced adherence to weekly cisplatin were more likely to have poor performance status. Further studies are warranted to improve the adherence to chemotherapy and outcomes.

Two by Two Factorial Design using Metformin and Curcumin for Second Primary Head and Neck Cancer Prevention Trial.

OBJECTIVE: The 2x2 factorial design is an effective method that allows for multiple comparisons, especially in the context of interactions between different interventions, without substantially increasing the required sample size. In view of the considerable preclinical evidence for Curcumin and Metformin in preventing the development and progression of head and neck squamous cell carcinoma (HNSCC), this study describes the protocol of the clinical trial towards applying the drug combination in prevention of second primary tumors. METHODS: We have applied the trial design to a large phase IIB/III double-blind, multi-centric, placebo-controlled, randomized clinical trial to determine the safety and efficacy of Metformin and Curcumin in the prevention of second primary tumours (SPT) of the aerodigestive tract following treatment of HNSCC (n=1,500) [Clinical Registry of India, CTRI/2018/03/012274]. Patients recruited in this trial will receive Metformin (with placebo), Curcumin (with placebo), Metformin, and Curcumin or placebo alone for a period of 36 months. The primary endpoint of this trial is the development of SPT, while the secondary endpoints are toxicities associated with the agents, incidence of recurrence, and identifying potential biomarkers. In this article, we discuss the 2x2 factorial design and how it applies to the head and neck cancer chemoprevention trial. CONCLUSION: 2x2 factorial design is an effective trial design for chemoprevention clinical trials where the effectiveness of multiple interventions needs to be tested parallelly.

Feasibility, Reliability, and Effectiveness of Oral cancer screening in South Asia and Southeast Asian countries: A systematic review and Meta-analysis.

OBJECTIVES: The incidence of oral cancer is significantly high in South Asia and Southeast Asia. Organized screening is an effective approach to early detection. The aim of this systematic review and meta-analysis was to evaluate the reliability, diagnostic accuracy, and effectiveness of visual oral screening by community health workers (CHWs) in identifying oral cancer/oral potentially malignant disorders (OPMDs) in this region. MATERIALS AND METHODS: We conducted a bibliographic search in PubMed, Scopus, the gray literature of Google Scholar, ProQuest dissertations, and additional manual searches. Twelve articles were included for qualitative synthesis and six for meta-analysis. Pooled sensitivity, specificity, diagnostic odds ratio (DOR), and forest plot analysis were performed. RESULTS: Meta-analysis showed CHWs identified 8% (n = 6365) as suspicious and 92% (n = 74,140) as normal. The diagnostic accuracy of visual oral screening by CHWs showed a sensitivity of 75% (CI: 74-76) and specificity of 97% (CI: 97-97) in the detection of OPMDs/oral cancer. Forest plots were obtained using a random effects model (DOR: 24.52 (CI: 22.65-26.55)) and SAUC: 0.96 (SE = 0.05). CONCLUSIONS: Oral visual examination by trained CHWs can be utilized for community screenings to detect oral cancer early. This approach can be used in primary healthcare to triage patients for further referral and management.

Rapid and Label-Free Histopathology of Oral Lesions Using Deep Learning Applied to Optical and Infrared Spectroscopic Imaging Data.

Oral potentially malignant disorders (OPMDs) are precursors to over 80% of oral cancers. Hematoxylin and eosin (H&E) staining, followed by pathologist interpretation of tissue and cellular morphology, is the current gold standard for diagnosis. However, this method is qualitative, can result in errors during the multi-step diagnostic process, and results may have significant inter-observer variability. Chemical imaging (CI) offers a promising alternative, wherein label-free imaging is used to record both the morphology and the composition of tissue and artificial intelligence (AI) is used to objectively assign histologic information. Here, we employ quantum cascade laser (QCL)-based discrete frequency infrared (DFIR) chemical imaging to record data from oral tissues. In this proof-of-concept study, we focused on achieving tissue segmentation into three classes (connective tissue, dysplastic epithelium, and normal epithelium) using a convolutional neural network (CNN) applied to three bands of label-free DFIR data with paired darkfield visible imaging. Using pathologist-annotated H&E images as the ground truth, we demonstrate results that are 94.5% accurate with the ground truth using combined information from IR and darkfield microscopy in a deep learning framework. This chemical-imaging-based workflow for OPMD classification has the potential to enhance the efficiency and accuracy of clinical oral precancer diagnosis.

Contrasting clinical outcomes and socio-economic impact of young versus elderly-onset oral squamous cell carcinoma, a novel health economic analysis.

OBJECTIVES: The incidence of young-onset oral squamous cell carcinoma (OSCC) is growing, even among non-smokers/drinkers. The effects of adverse histopathological features on long-term oncologic outcomes between the young and old are controversial and confounded by significant heterogeneity. Few studies have evaluated the socio-economic impact of premature mortality from OSCC. Our study seeks to quantify these differences and their economic impact on society. MATERIALS AND METHODS: Four hundred and seventy-eight young (<45 years) and 1660 old patients (≥45 years) with OSCC were studied. Logistic regression determined predictors of recurrence and death. Survival analysis was calculated via the Kaplan-Meier method. A separate health economic analysis was conducted for India and Singapore. Years of Potential Productive Life Lost (YPPLL) were estimated with the Human Capital Approach, and premature mortality cost was derived using population-level data. RESULTS: Adverse histopathological features were seen more frequently in young OSCC: PNI (42.9% vs. 35%, p = 0.002), LVI (22.4% vs. 17.3%, p = 0.013) and ENE (36% vs. 24.5%, p < 0.001). Although 5-year OS/DSS were similar, the young cohort had received more intensive adjuvant therapy (CCRT 26.9% vs. 16.6%, p < 0.001). Among Singaporean males, the premature mortality cost per death was US $396,528, and per YPPLL was US $45,486. This was US $397,402 and US $38,458 for females. Among Indian males, the premature mortality cost per death was US $30,641, and per YPPLL was US $595. This was US $ 21,038 and US $305 for females. CONCLUSION: Young-onset OSCC is an aggressive disease, mitigated by the ability to receive intensive adjuvant treatment. From our loss of productivity analysis, the socio-economic costs from premature mortality are substantial. Early cancer screening and educational outreach campaigns should be tailored to this cohort. Alongside, more funding should be diverted to genetic research, developing novel biomarkers and improving the efficacy of adjuvant treatment in OSCC.

Whole exome sequencing uncovers HRAS mutations as potential mediators of resistance to metronomic chemotherapy.

OBJECTIVES: The aim of this pilot study is to identify the genetic factors that contribute to the response of metronomic chemotherapy in head and neck squamous cell carcinoma (HNSCC) patients using whole-exome sequencing (WES). This study would facilitate the identification of predictive biomarkers, which would enable personalized treatment strategies and improve treatment outcomes for patients with HNSCC. MATERIALS AND METHODS: We have selected patients with recurrent head and neck cancer who underwent metronomic chemotherapy. Sequential tumor biopsies were collected from the patients at different stages of treatment to capture the genomic alterations and tumor evolution during metronomic chemotherapy and sequenced using WES. RESULTS: We identified several known HNSCC hallmark genes reported in COSMIC, including KMT2B, NOTCH1, FAT1, TP53, HRAS, CASP8, and CDKN2A. Copy number alteration analysis revealed amplifications and deletions in several oncogenic and tumor suppressor genes. COSMIC Mutational Signature 15 associated with defective DNA mismatch repair was enriched in 73% of HNSCC samples. Further, the comparison of genomic alterations between responders and non-responders identified HRAS gene uniquely mutated in non-responders that could potentially contribute to resistance against metronomic chemotherapy. DISCUSSION: Our findings corroborate the molecular heterogeneity of recurrent HNSCC tumors and establish an association between HRAS mutations and resistance to metronomic chemotherapy, suggesting HRAS as a potential therapeutic target. Combining HRAS inhibitors with metronomic regimens could improve treatment sensitivity in HRAS-mutated HNSCC patients. Further studies are needed to fully elucidate the genomic mechanisms underlying the response to metronomic chemotherapy.

Inter-observer agreement among specialists in the diagnosis of oral potentially malignant disorders and oral cancer using store-and-forward technology.

OBJECTIVES: Oral cancer is a leading cause of morbidity and mortality. Screening and mobile Health (mHealth)-based approach facilitates early detection remotely in a resource-limited settings. Recent advances in eHealth technology have enabled remote monitoring and triage to detect oral cancer in its early stages. Although studies have been conducted to evaluate the diagnostic efficacy of remote specialists, to our knowledge, no studies have been conducted to evaluate the consistency of remote specialists. The aim of this study was to evaluate interobserver agreement between specialists through telemedicine systems in real-world settings using store-and-forward technology. MATERIALS AND METHODS: The two remote specialists independently diagnosed clinical images (n=822) from image archives. The onsite specialist diagnosed the same participants using conventional visual examination, which was tabulated. The diagnostic accuracy of two remote specialists was compared with that of the onsite specialist. Images that were confirmed histopathologically were compared with the onsite diagnoses and the two remote specialists. RESULTS: There was moderate agreement (k= 0.682) between two remote specialists and (k= 0.629) between the onsite specialist and two remote specialists in the diagnosis of oral lesions. The sensitivity and specificity of remote specialist 1 were 92.7% and 83.3%, respectively, and those of remote specialist 2 were 95.8% and 60%, respectively, each compared with histopathology. CONCLUSION: The diagnostic accuracy of the two remote specialists was optimal, suggesting that "store and forward" technology and telehealth can be an effective tool for triage and monitoring of patients. CLINICAL RELEVANCE: Telemedicine is a good tool for triage and enables faster patient care in real-world settings.

CD44-SNA1 integrated cytopathology for delineation of high grade dysplastic and neoplastic oral lesions.

The high prevalence of oral potentially-malignant disorders exhibits diverse severity and risk of malignant transformation, which mandates a Point-of-Care diagnostic tool. Low patient compliance for biopsies underscores the need for minimally-invasive diagnosis. Oral cytology, an apt method, is not clinically applicable due to a lack of definitive diagnostic criteria and subjective interpretation. The primary objective of this study was to identify and evaluate the efficacy of biomarkers for cytology-based delineation of high-risk oral lesions. A comprehensive systematic review and meta-analysis of biomarkers recognized a panel of markers (n: 10) delineating dysplastic oral lesions. In this observational cross sectional study, immunohistochemical validation (n: 131) identified a four-marker panel, CD44, Cyclin D1, SNA-1, and MAA, with the best sensitivity (>75%; AUC>0.75) in delineating benign, hyperplasia, and mild-dysplasia (Low Risk Lesions; LRL) from moderate-severe dysplasia (High Grade Dysplasia: HGD) along with cancer. Independent validation by cytology (n: 133) showed that expression of SNA-1 and CD44 significantly delineate HGD and cancer with high sensitivity (>83%). Multiplex validation in another cohort (n: 138), integrated with a machine learning model incorporating clinical parameters, further improved the sensitivity and specificity (>88%). Additionally, image automation with SNA-1 profiled data set also provided a high sensitivity (sensitivity: 86%). In the present study, cytology with a two-marker panel, detecting aberrant glycosylation and a glycoprotein, provided efficient risk stratification of oral lesions. Our study indicated that use of a two-biomarker panel (CD44/SNA-1) integrated with clinical parameters or SNA-1 with automated image analysis (Sensitivity >85%) or multiplexed two-marker panel analysis (Sensitivity: >90%) provided efficient risk stratification of oral lesions, indicating the significance of biomarker-integrated cytopathology in the development of a Point-of-care assay.

Extended Level IV Neck Dissection for Limited Prophylactic Clearance of Level V in Node-Positive Papillary Thyroid Carcinoma: a Homogenous Study Population.

There is near consensus that prophylactic lateral neck dissection has no role in the management of differentiated thyroid cancer, but the extent of lateral neck dissection in differentiated thyroid cancer remains controversial, especially whether level V should be addressed or not. There is lot of heterogeneity in reporting of the management of level V in papillary thyroid cancer. We at our Institute address the lateral neck positive papillary thyroid cancer with selective neck dissection involving levels II-IV, performing extended level IV dissection with inclusion of the triangular area delineated by the sternocleidomastoid muscle, the clavicle, and the perpendicular line drawn to the clavicle from the point where the horizontal line at the level of cricoid cuts the posterior border of sternocleidomastoid muscle. Retrospective analysis of the departmental data set related to thyroidectomy with lateral neck dissection from 2013 to mid-2019 for papillary thyroid cancer, was carried out. Patients with recurrent papillary thyroid cancer were excluded as were patients with involvement of level V. Data related to the demography of patients, histological diagnosis, and postoperative complications were compiled and summarized. Note was made of the incidence of ipsilateral neck recurrence and the neck level involved with recurrence noted. Data was analyzed for fifty-two patients of non-recurrent papillary thyroid cancer who had undergone total thyroidectomy and lateral neck dissection involving levels II-IV, with extended dissection at level IV. It should be noted that none of the patients had clinical involvement of level V. Only two patients had lateral neck recurrence, both the recurrences were in level III, one on the ipsilateral side and the other on the contralateral side. Recurrence in the central compartment was noted in two patients, with one of these patients also having ipsilateral level III recurrence. One of the patients had distal metastasis to the lungs. Transient paresis of the unilateral vocal cords was noted in seven patients which got resolved within 2 months in all of them. Transient hypocalcemia was noted in four patients. Although our series has a small sample size with limited follow-up, it is one of the few studies in which prophylactic level V dissection has been studied in a homogenous study population of non-recurrent papillary thyroid cancer. Our study has shown that prophylactic dissection of level V may have a limited role, but further large multi-institutional studies need to be carried out to come up with a definite answer.

Association of Body Mass Index With Outcomes Among Patients With Head and Neck Cancer Treated With Chemoradiotherapy.

Importance: Combined modality therapy, such as chemoradiotherapy, often results in significant morbidity among patients with head and neck cancer. Although the role of body mass index (BMI) varies based on cancer subtypes, its association with treatment response, tumor recurrence, and survival outcomes among patients with head and neck cancer remains unclear. Objective: To evaluate the role of BMI in treatment response, tumor recurrence, and survival outcomes among patients with head and neck cancer undergoing chemoradiotherapy. Design, Setting, and Participants: This retrospective, observational, single-institution cohort study conducted at a comprehensive cancer center included 445 patients with nonmetastatic head and neck cancer who underwent chemoradiotherapy from January 1, 2005, to January 31, 2021. Exposure: Normal vs overweight or obese BMI. Main Outcomes and Measures: Metabolic response after chemoradiotherapy, locoregional failure (LRF), distant failure (DF), overall survival (OS), and progression-free survival (PFS), with Bonferroni correction used to adjust for multiple comparisons and P < .025 being considered statistically significant. Results: A total of 445 patients (373 men [83.8%]; median age, 61 years [IQR, 55-66 years]; 107 [24.0%] with normal BMI, 179 [40.2%] with overweight BMI, and 159 [35.7%] with obese BMI) were included for analysis. Median follow-up was 48.1 months (IQR, 24.7-74.9 months). On Cox proportional hazards regression multivariable analysis, only overweight BMI was associated with improved OS (5-year OS, 71.5% vs 58.4%; adjusted hazard ratio [AHR], 0.59 [95% CI, 0.39-0.91]; P = .02) and PFS (5-year PFS, 68.3% vs 50.8%; AHR, 0.51 [95% CI, 0.34-0.75]; P < .001). On logistic multivariable analysis, overweight BMI (91.6% vs 73.8%; adjusted odds ratio [AOR], 0.86 [95% CI, 0.80-0.93]; P < .001) and obese BMI (90.6% vs 73.8%; AOR, 0.89 [95% CI, 0.81-0.96]; P = .005) were associated with complete metabolic response on follow-up positron emission tomography-computed tomography after treatments. On Fine-Gray multivariable analysis, overweight BMI was associated with reduction in LRF (5-year LRF, 7.0% vs 25.9%; AHR, 0.30 [95% CI, 0.12-0.71]; P = .01), but not DF (5-year DF, 17.4% vs 21.5%; AHR, 0.92 [95% CI, 0.47-1.77]; P = .79). Obese BMI was not associated with LRF (5-year LRF, 10.4% vs 25.9%; AHR, 0.63 [95% CI, 0.29-1.37]; P = .24) or DF (5-year DF, 15.0% vs 21.5%; AHR, 0.70 [95% CI, 0.35-1.38]; P = .30). Conclusion: In this cohort study of patients with head and neck cancer, when compared with normal BMI, overweight BMI was an independent factor favorably associated with complete response after treatments, OS, PFS, and LRF. Further investigations are warranted to improve understanding on the role of BMI among patients with head and neck cancer.

Association of pre-treatment lymphocyte-monocyte ratio with survival outcome in patients with head and neck cancer treated with chemoradiation.

BACKGROUND: Given the role of systematic inflammation in cancer progression, lymphocyte-monocyte ratio (LMR) from peripheral blood has been suggested as a biomarker to assess the extent of inflammation in several solid malignancies. However, the role of LMR as a prognostic factor in head and neck cancer was unclear in several meta-analyses, and there is a paucity of literature including patients in North America. We performed an observational cohort study to evaluate the association of LMR with survival outcomes in North American patients with head and neck cancer. METHODS: A single-institution, retrospective database was queried for patients with non-metastatic head and neck cancer who underwent definitive chemoradiation from June 2007 to April 2021 at the Roswell Park Comprehensive Cancer Center. Primary endpoints were overall survival (OS) and cancer-specific survival (CSS). The association of LMR with OS and CSS was examined using nonlinear Cox proportional hazard model using restricted cubic splines (RCS). Cox multivariable analysis (MVA) and Kaplan-Meier method were used to analyze OS and CSS. Pre-radiation LMR was then stratified into high and low based on its median value. Propensity scored matching was used to reduce the selection bias. RESULTS: A total of 476 patients met our criteria. Median follow up was 45.3 months (interquartile range 22.8-74.0). The nonlinear Cox regression model showed that low LMR was associated with worse OS and CSS in a continuous fashion without plateau for both OS and CSS. On Cox MVA, higher LMR as a continuous variable was associated with improved OS (adjusted hazard ratio [aHR] 0,90, 95% confidence interval [CI] 0.82-0.99, p = 0.03) and CSS (aHR 0.83, 95% CI 0.72-0.95, p = 0.009). The median value of LMR was 3.8. After propensity score matching, a total of 186 pairs were matched. Lower LMR than 3.8 remained to be associated with worse OS (HR 1.59, 95% CI 1.12-2.26, p = 0.009) and CSS (HR 1.68, 95% CI 1.08-2.63, p = 0.02). CONCLUSION: Low LMR, both as a continuous variable and dichotomized variable, was associated with worse OS and CSS. Further studies would be warranted to evaluate the role of such prognostic marker to tailor interventions.

Inter-observer agreement among specialists in the diagnosis of Oral Potentially Malignant Disorders and Oral Cancer using Store-and-Forward technology.

Oral Cancer is one of the most common causes of morbidity and mortality. Screening and mobile Health (mHealth) based approach facilitates remote early detection of Oral cancer in a resource-constrained settings. The emerging eHealth technology has aided specialist reach to rural areas enabling remote monitoring and triaging to downstage Oral cancer. Though the diagnostic accuracy of the remote specialist has been evaluated, there are no studies evaluating the consistency among the remote specialists, to the best of our knowledge. The purpose of the study was to evaluate the interobserver agreement between the specialists through telemedicine systems in real-world settings using store and forward technology. Two remote specialists independently diagnosed the clinical images from image repositories, and the diagnostic accuracy was compared with onsite specialist and histopathological diagnosis when available. Moderate agreement (k = 0.682) between two remote specialists and (k = 0.629) between the onsite specialist and two remote specialists in diagnosing oral lesions. The sensitivity and specificity of remote specialist 1 were 92.7% and 83.3%, whereas remote specialist 2 was 95.8% and 60%, respectively, compared to histopathology. The store and forward technology and telecare can be effective tools in triaging and surveillance of patients.

BCA101 Is a Tumor-Targeted Bifunctional Fusion Antibody That Simultaneously Inhibits EGFR and TGFß Signaling to Durably Suppress Tumor Growth.

The EGFR and TGFß signaling pathways are important mediators of tumorigenesis, and cross-talk between them contributes to cancer progression and drug resistance. Therapies capable of simultaneously targeting EGFR and TGFß could help improve patient outcomes across various cancer types. Here, we developed BCA101, an anti-EGFR IgG1 mAb linked to an extracellular domain of human TGFßRII. The TGFß "trap" fused to the light chain in BCA101 did not sterically interfere with its ability to bind EGFR, inhibit cell proliferation, or mediate antibody-dependent cellular cytotoxicity. Functional neutralization of TGFß by BCA101 was demonstrated by several in vitro assays. BCA101 increased production of proinflammatory cytokines and key markers associated with T-cell and natural killer-cell activation, while suppressing VEGF secretion. In addition, BCA101 inhibited differentiation of naïve CD4+ T cells to inducible regulatory T cells (iTreg) more strongly than the anti-EGFR antibody cetuximab. BCA101 localized to tumor tissues in xenograft mouse models with comparable kinetics to cetuximab, both having better tumor tissue retention over TGFß "trap." TGFß in tumors was neutralized by approximately 90% in animals dosed with 10 mg/kg of BCA101 compared with 54% in animals dosed with equimolar TGFßRII-Fc. In patient-derived xenograft mouse models of head and neck squamous cell carcinoma, BCA101 showed durable response after dose cessation. The combination of BCA101 and anti-PD1 antibody improved tumor inhibition in both B16-hEGFR-expressing syngeneic mouse models and in humanized HuNOG-EXL mice bearing human PC-3 xenografts. Together, these results support the clinical development of BCA101 as a monotherapy and in combination with immune checkpoint therapy. SIGNIFICANCE: The bifunctional mAb fusion design of BCA101 targets it to the tumor microenvironment where it inhibits EGFR and neutralizes TGFß to induce immune activation and to suppress tumor growth.

Interpretable and Reliable Oral Cancer Classifier with Attention Mechanism and Expert Knowledge Embedding via Attention Map.

Convolutional neural networks have demonstrated excellent performance in oral cancer detection and classification. However, the end-to-end learning strategy makes CNNs hard to interpret, and it can be challenging to fully understand the decision-making procedure. Additionally, reliability is also a significant challenge for CNN based approaches. In this study, we proposed a neural network called the attention branch network (ABN), which combines the visual explanation and attention mechanisms to improve the recognition performance and interpret the decision-making simultaneously. We also embedded expert knowledge into the network by having human experts manually edit the attention maps for the attention mechanism. Our experiments have shown that ABN performs better than the original baseline network. By introducing the Squeeze-and-Excitation (SE) blocks to the network, the cross-validation accuracy increased further. Furthermore, we observed that some previously misclassified cases were correctly recognized after updating by manually editing the attention maps. The cross-validation accuracy increased from 0.846 to 0.875 with the ABN (Resnet18 as baseline), 0.877 with SE-ABN, and 0.903 after embedding expert knowledge. The proposed method provides an accurate, interpretable, and reliable oral cancer computer-aided diagnosis system through visual explanation, attention mechanisms, and expert knowledge embedding.

Association of Pack-Years of Cigarette Smoking With Survival and Tumor Progression Among Patients Treated With Chemoradiation for Head and Neck Cancer.

Importance: After 10 pack-years of smoking was initially established as a threshold for risk stratification, subsequent clinical trials incorporated it to identify candidates for treatment deintensification. However, several recent studies were unable to validate this threshold externally, and the threshold for smoking exposure remains unclear. Objective: To estimate the threshold of pack-years of smoking associated with survival and tumor recurrence among patients with head and neck cancer. Design, Setting, and Participants: This single-institution, cohort study included patients with nonmetastatic head and neck cancer receiving chemoradiation from January 2005 to April 2021. Data were analyzed from January to April 2022. Exposures: Heavy vs light smoking using 22 pack-years as a threshold based on maximizing log-rank test statistic. Main Outcomes and Measures: Overall survival (OS), progression-free survival (PFS), locoregional failure (LRF), and distant failure (DF). Results: A total of 518 patients (427 male [82.4%]; median [IQR] age, 61 [55-66] years) were included. Median (IQR) follow-up was 44.1 (22.3-72.8) months. A nonlinear Cox regression model using restricted cubic splines showed continuous worsening of OS and PFS outcomes as pack-years of smoking increased. The threshold of pack-years to estimate OS and PFS was 22. Cox multivariable analysis (MVA) showed that more than 22 pack-years was associated with worse OS (adjusted hazard ratio [aHR] 1.57; 95% CI, 1.11-2.22; P = .01) and PFS (aHR, 1.38; 95% CI, 1.00-1.89; P = .048). On Fine-Gray MVA, heavy smokers were associated with DF (aHR, 1.71; 95% CI, 1.02-2.88; P = .04), but not LRF (aHR, 1.07; 95% CI, 0.61-1.87; P = .82). When 10 pack-years of smoking were used as a threshold, there was no association for OS (aHR, 1.23; 95% CI, 0.83-1.81; P = .30), PFS (aHR, 1.11; 95% CI, 0.78-1.57; P = .56), LRF (aHR, 1.19; 95% CI, 0.64-2.21; P = .58), and DF (aHR, 1.45; 95% CI, 0.82-2.56; P = .20). Current smoking was associated with worse OS and PFS only among human papillomavirus (HPV)-positive tumors (OS: aHR, 2.81; 95% CI, 1.26-6.29; P = .01; PFS: aHR, 2.51; 95% CI, 1.22-5.14; P = .01). Conclusions and Relevance: In this cohort study of patients treated with definitive chemoradiation, 22 pack-years of smoking was associated with survival and distant metastasis outcomes. Current smoking status was associated with adverse outcomes only among patients with HPV-associated head and neck cancer.

Exploring uncertainty measures in convolutional neural network for semantic segmentation of oral cancer images.

Significance: Oral cancer is one of the most prevalent cancers, especially in middle- and low-income countries such as India. Automatic segmentation of oral cancer images can improve the diagnostic workflow, which is a significant task in oral cancer image analysis. Despite the remarkable success of deep-learning networks in medical segmentation, they rarely provide uncertainty quantification for their output. Aim: We aim to estimate uncertainty in a deep-learning approach to semantic segmentation of oral cancer images and to improve the accuracy and reliability of predictions. Approach: This work introduced a UNet-based Bayesian deep-learning (BDL) model to segment potentially malignant and malignant lesion areas in the oral cavity. The model can quantify uncertainty in predictions. We also developed an efficient model that increased the inference speed, which is almost six times smaller and two times faster (inference speed) than the original UNet. The dataset in this study was collected using our customized screening platform and was annotated by oral oncology specialists. Results: The proposed approach achieved good segmentation performance as well as good uncertainty estimation performance. In the experiments, we observed an improvement in pixel accuracy and mean intersection over union by removing uncertain pixels. This result reflects that the model provided less accurate predictions in uncertain areas that may need more attention and further inspection. The experiments also showed that with some performance compromises, the efficient model reduced computation time and model size, which expands the potential for implementation on portable devices used in resource-limited settings. Conclusions: Our study demonstrates the UNet-based BDL model not only can perform potentially malignant and malignant oral lesion segmentation, but also can provide informative pixel-level uncertainty estimation. With this extra uncertainty information, the accuracy and reliability of the model's prediction can be improved.

Consensus guidelines on management of oral potentially malignant disorders.

Oral cancer is usually preceded by oral potentially malignant disorders (OPMDs) and early detection can downstage the disease. The majority of OPMDs are asymptomatic in early stages and can be detected on routine oral examination. Though only a proportion of OPMDs may transform to oral squamous cell carcinoma (OSCC), they may serve as a surrogate clinical lesion to identify individuals at risk of developing OSCC. Currently, there is a scarcity of scientific evidence on specific interventions and management of OPMDs and there is no consensus regarding their management. A consensus meeting with a panel of experts was convened to frame guidelines for clinical practices and recommendations for management strategies for OPMDs. A review of literature from medical databases was conducted to provide the best possible evidence and provide recommendations in management of OPMDs.

Oral epithelial cell segmentation from fluorescent multichannel cytology images using deep learning.

BACKGROUND AND OBJECTIVES: Cytology is a proven, minimally-invasive cancer screening and surveillance strategy. Given the high incidence of oral cancer globally, there is a need to develop a point-of-care, automated, cytology-based screening tool. Oral cytology image analysis has multiple challenges such as, presence of debris, blood cells, artefacts, and clustered cells, which necessitate a skilled expertise for single-cell detection of atypical cells for diagnosis. The main objective of this study is to develop a semantic segmentation model for Single Epithelial Cell (SEC) separation from fluorescent, multichannel, microscopic oral cytology images and classify the segmented images. METHODS: We have used multi-channel, fluorescent, microscopic images (number of images; n = 2730), which were stained differentially for cytoplasm and nucleus. The cytoplasmic and cell membrane markers used in the study were Mackia Amurensis Agglutinin (MAA; n: 2364) and Sambucus Nigra Agglutinin-1 (SNA-1; n: 366) with a nuclear stain DAPI. The cytology images were labelled for SECs, cluster of cells, artefacts, and blood cells. In this study, we used encoder-decoder models based on the well-established U-Net architecture, modified U-Net and ResNet-34 for multi-class segmentation. The experiments were performed with different class combinations of data to reduce imbalance. The derived MAA dataset (n: 14,706) of SEC, cluster, and artefacts/blood cells were used for developing a classification model. InceptionV3 model and a new custom Convolutional-Neural-Network (CNN) model (Artefact-Net) were trained to classify SNA-1 marker stained segmented images (n:6101). For segmentation models, Intersection Over Union (IoU) and F1 score were used as the evaluation matrices, while the classification models were evaluated using the conventional classification metrics like precision, recall and F1-Score. RESULTS: The U-Net and the modified U-Net models gave the best IoU overall (0.73-0.76) as well as for SEC segmentation (079). The images segmented using the modified U-Net model were classified by Artefact-Net and Inception V3 model with F1 scores of 0.96 and 0.95 respectively. The Artefact-Net, when compared to InceptionV3, provided a better precision and F1 score in classifying clusters (Precision: 0.91 vs 0.80; F1: 0.91 vs 0.86). CONCLUSION: This study establishes a pipeline for SEC segmentation with the segmented component containing only single cells. The pipline will enable automated, cytology-based early detection with reduced bias.

A Distributed Cancer Care Model with a Technology-Driven Hub-and-Spoke and further Spoke Hierarchy: Findings from a Pilot Implementation Programme in Kerala, India.

BACKGROUND: The technology enabled distributed model in Kerala is based on an innovative partnership model between Karkinos Healthcare and private health centers. The model is designed to address the barriers to cancer screening by generating demand and by bringing together the private health centers and service providers at various levels to create a network for continued care. This paper describes the implementation process and presents some preliminary findings.  Methods: The model follows the hub-and-spoke and further spoke framework. In the pilot phases, from July 2021 to December 2021, five private health centers (partners) collaborated with Karkinos Healthcare across two districts in Kerala. Screening camps were organized across the districts at the community level where the target groups were administered a risk assessment questionnaire followed by screening tests at the spoke hospitals based on a defined clinical protocol. The screened positive patients were examined further for confirmatory diagnosis at the spoke centers. Patients requiring chemotherapy or minor surgeries were treated at the spokes. For radiation therapy and complex surgeries the patients were referred to the hubs. RESULTS: A total of 2,459 individuals were screened for cancer at the spokes and 299 were screened positive. Capacity was built at the spokes for cancer surgery and chemotherapy. A total of 189 chemotherapy sessions and 17 surgeries were performed at the spokes for cancer patients. 70 patients were referred to the hub. CONCLUSION: Initial results demonstrate the ability of the technology Distributed Cancer Care Network (DCCN) system to successfully screen and detect cancer and to converge the actions of various private health facilities towards providing a continuum of cancer care. The lessons learnt from this study will be useful for replicating the process in other States.

Defining the optimal threshold and prognostic utility of pre-treatment hemoglobin level as a biomarker for survival outcomes in head and neck cancer patients receiving chemoradiation.

OBJECTIVES: We sought to define the optimal threshold for anemia in North American head and neck cancer patients and evaluate its role as a prognostic biomarker. MATERIALS AND METHODS: A single-institution database was queried for patients with head and neck cancer who underwent chemoradiation from January 2005 to April 2021. An optimal threshold of hemoglobin (Hgb) level was defined based on maximum log-rank test statistic. Cox multivariable analysis (MVA), Kaplan-Meier, and propensity score matching were performed to evaluate treatment outcomes. RESULTS: A total of 496 patients were identified. Threshold for Hgb was determined to be 11.4 for both overall survival (OS) and progression-free survival (PFS). Low Hgb was associated with worse OS (adjusted hazards ratio [aHR] 2.41, 95 % confidence interval [CI] 1.53-3.80, p < 0.001) and PFS (aHR 2.01, 95 % CI 1.30-3.11, p = 0.002). Similar findings were observed among 39 matched pairs for OS (5-year OS 22.3 % vs 49.0 %; HR 2.22, 95 % CI 1.23-4.03, p = 0.008) and PFS (5-year PFS 24.3 % vs 39.1 %; HR 1.78, 95 % CI 1.02-3.12, p = 0.04). Among those with HPV-negative tumors, low Hgb was associated with worse OS (aHR 13.90, 95 % CI 4.66-41.44, p < 0.001) and PFS (aHR 5.24, 95 % CI 2.09-13.18, p < 0.001). However, among those with HPV-positive tumors, low Hgb was not associated with both OS (aHR 1.75, 95 % CI 0.60-5.09, p = 0.31) and PFS (aHR 1.13, 95 % CI 0.41-3.14, p = 0.82). CONCLUSION AND RELEVANCE: Low Hgb below 11.4 was an independent adverse prognostic factor for worse survival. It was also prognostic among patients with HPV-negative tumors, but not for HPV-positive tumors.