Specimen-Based Resection Margins and Local Control during Transoral Robotic Surgery for Oropharyngeal HPV-Mediated Squamous Cell Carcinoma.

OBJECTIVES: The aim of the study was to investigate the association of surgical margin conditions, including positive specimen margins revised to negative relative to local recurrence, disease-free survival, and overall survival (OS) within a cohort of HPV-mediated oropharyngeal squamous cell carcinoma (OPSCC) who underwent en bloc resection via transoral robotic surgery (TORS). MATERIALS AND METHODS: Retrospective cohort of patients with untreated HPV-mediated OPSCC cT1 or T2 undergoing TORS resection between October 2014 and March 2020. The methodologic description of our interdisciplinary institutional approach, number of cut-through margins (CTMs) during intraoperative consultation, percentage of final positive margin cases, and disease-free survival and OS stratified by margin status and margin tumor-free distance is identified. RESULTS: 135 patients with primary cT1/T2 HPV-mediated OPSCC met inclusion criteria. Twenty-eight of 135 (20.7%) specimens revealed CTM and were revised during the same operative setting. Three of 135 (2.2%) surgical cases had positive final margin status. Local control rate was 97%. On univariate analysis, margin distance did not impact OS. CTM and final positive margins had lower OS than initially negative margins (p = 0.044). Pathologic N-stage significantly impacted OS (p < 0.001). CONCLUSIONS: High local control rate and low final positive margin status confound the study of specimen margin-based techniques in HPV-mediated OPSCC resected en bloc with TORS. Pathologic N-stage may impact OS more than margin status. Larger numbers are needed to confirm differences.

Machine Learning to Predict Treatment in Oropharyngeal Squamous Cell Carcinoma.

OBJECTIVES: This study seeks to (1) demonstrate how machine learning (ML) can be used for prediction modeling by predicting the treatment patients with T1-2, N0-N1 oropharyngeal squamous cell carcinoma (OPSCC) receive and (2) assess the impact patient, socioeconomic, regional, and institutional factors have in the treatment of this population. METHODS: A retrospective cohort of adults diagnosed with T1-2, N0-N1 OPSCC from 2004 to 2013 was obtained using the National Cancer Database. The data was split into 80/20 distribution for training and testing, respectively. Various ML algorithms were explored for development. Area under the curve (AUC), accuracy, precision, and recall were calculated for the final model. RESULTS: Among the 19,111 patients in the study, the mean (standard deviation) age was 61.3 (10.8) years, 14,034 (73%) were male, and 17,292 (91%) were white. Surgery was the primary treatment in 9,533 (50%) cases and radiation in 9,578 (50%) cases. The model heavily utilized T-stage, primary site, N-stage, grade, and type of treatment facility to predict the primary treatment modality. The final model yielded an AUC of 78% (95% CI, 77-79%), accuracy of 71%, precision of 72%, and recall of 71%. CONCLUSION: This study created a ML model utilizing clinical variables to predict primary treatment modality for T1-2, N0-N1 OPSCC. This study demonstrates how ML can be used for prediction modeling while also highlighting that tumor and facility realted variables impact the decision making process on a national level.

Lateral thoracic artery as recipient vessel for head and neck free flap reconstruction in the vessel depleted neck: A case report.

Vessel depleted necks present a challenge to identifying suitable recipient vessels for microvascular head and neck reconstruction. Many alternative recipient vessels have been described. The purpose of this report is to describe the feasibility of using the lateral thoracic artery as a recipient vessel for head and neck free flap reconstruction in vessel depleted necks. In this report we describe surgery for a 62 year old male with osteoradionecrosis of the right mandibular body in which we performed right segmental mandibulectomy with free fibular flap reconstruction in a vessel depleted neck. We used the lateral thoracic artery which was ~10 cm in length. It provided good reach to the neck, proper blood flow, and acceptable vessel diameter of ~1.5 mm at 6 cm above the clavicle. The patient had an uncomplicated postoperative course and the flap was viable and well healed at 2 months follow-up. The lateral thoracic artery could be considered as one of the options for recipient vessels for microvascular reconstruction in patients with vessel depleted necks.

Defining the Role of Free Flaps for Transoral Robotic Surgery.

BACKGROUND: Transoral surgical techniques for oropharyngeal tumors have been widely accepted, yet often results in a significant functional deficit. Current reports on the safety, feasibility, and swallowing performance after microvascular reconstruction are limited to small volume case series. MATERIALS AND METHODS: Retrospective review of 42 consecutive patients, between December 2013 and May 2016, who underwent transoral robotic surgery oropharyngectomy followed by microvascular reconstruction. RESULTS: Swallowing outcomes postoperatively resulted in 39 (93%) of patients tolerating oral intake postoperatively, with 13 (87%) of 15 patients at 1-year follow-up consuming an entirely oral diet. Thirty-eight (95%) of 40 patients who underwent a tracheostomy at the time of surgery were ultimately decannulated. No patients experienced complete flap failure in the current study. CONCLUSIONS: Minimally invasive transoral surgical techniques have offered the opportunity to minimize surgical morbidity and potentially deintensify adjuvant therapies. Reconstructive options have evolved to match surgical advances seen with robotic surgeries of oropharyngeal cancers. Microvascular reconstruction has been indicated in select patients including those with extensive soft palate resection, primary tumor abutment of the medial pterygoid musculature, exposure of internal carotid artery vasculature, prior radiation therapy, or a significant defect of the oropharyngeal sphincter. Select patients, based on previously identified criteria, were preoperatively identified as suitable candidates for microvascular reconstruction of oropharyngeal defects. This study demonstrates that complex transoral robotic surgical defects are amenable to microvascular reconstructive in carefully selected patients.

Quantitative measurements of radiation-induced fibrosis for head and neck cancer: A narrative review.

Objectives: To provide a comprehensive summary of the different modalities available to measure soft tissue fibrosis after radiotherapy in head and neck cancer patients. Data Sources: PubMed, Scopus, and Web of Sciences. Review Methods: A search was conducted using a list of medical subject headings and terms related to head and neck oncology, radiation fibrosis, and quantitative measurements, including bioimpedance, MRI, and ultrasound. Original research related to quantitative measurement of neck fibrosis post-radiotherapy was included without time constraints, while reviews, case reports, non-English texts, and inaccessible studies were excluded. Discrepancies during the review were resolved by discussing with the senior author until consensus was reached. Results: A total of 284 articles were identified and underwent title and abstract screening. Seventeen articles had met our criteria for full-text review based on relevance, of which nine had met our inclusion criteria. Young's modulus (YM) and viscoelasticity measures have demonstrated efficacy in quantifying neck fibrosis, with fibrotic tissues displaying significantly higher YM values and altered viscoelastic properties such as increased stiffness rate-sensitivity and prolonged stress-relaxation post-radiation. Intravoxel incoherent motion offers detailed insights into tissue changes by assessing the diffusion of water molecules and blood perfusion, thereby differentiating fibrosed from healthy tissues. Shear wave elastography has proven to be an effective technique for quantifying radiation-induced fibrosis in the head and neck region by measuring shear wave velocity. Conclusion: There are various modalities to measure radiation-induced fibrosis, each with its unique strengths and limitations. Providers should be aware of these implications and decide on methodologies based on their specific clinical workflow. Level of Evidence: Step 5.

Exploring the Role of Artificial Intelligence Chatbots in Preoperative Counseling for Head and Neck Cancer Surgery.

OBJECTIVE: To evaluate the potential use of artificial intelligence (AI) chatbots, such as ChatGPT, in preoperative counseling for patients undergoing head and neck cancer surgery. STUDY DESIGN: Cross-Sectional Survey Study. SETTING: Single institution tertiary care center. METHODS: ChatGPT was used to generate presurgical educational information including indications, risks, and recovery time for five common head and neck surgeries. Chatbot-generated information was compared with information gathered from a simple browser search (first publicly available website excluding scholarly articles). The accuracy of the information, readability, thoroughness, and number of errors were compared by five experienced head and neck surgeons in a blinded fashion. Each surgeon then chose a preference between the two information sources for each surgery. RESULTS: With the exception of total word count, ChatGPT-generated pre-surgical information has similar readability, content of knowledge, accuracy, thoroughness, and numbers of medical errors when compared to publicly available websites. Additionally, ChatGPT was preferred 48% of the time by experienced head and neck surgeons. CONCLUSION: Head and neck surgeons rated ChatGPT-generated and readily available online educational materials similarly. Further refinement in AI technology may soon open more avenues for patient counseling. Future investigations into the medical safety of AI counseling and exploring patients' perspectives would be of strong interest. LEVEL OF EVIDENCE: N/A. Laryngoscope, 134:2757-2761, 2024.

Predicting reoperation and readmission for head and neck free flap patients using machine learning.

BACKGROUND: To develop machine learning (ML) models predicting unplanned readmission and reoperation among patients undergoing free flap reconstruction for head and neck (HN) surgery. METHODS: Data were extracted from the 2012-2019 NSQIP database. eXtreme Gradient Boosting (XGBoost) was used to develop ML models predicting 30-day readmission and reoperation based on demographic and perioperative factors. Models were validated using 2019 data and evaluated. RESULTS: Four-hundred and sixty-six (10.7%) of 4333 included patients were readmitted within 30 days of initial surgery. The ML model demonstrated 82% accuracy, 63% sensitivity, 85% specificity, and AUC of 0.78. Nine-hundred and four (18.3%) of 4931 patients underwent reoperation within 30 days of index surgery. The ML model demonstrated 62% accuracy, 51% sensitivity, 64% specificity, and AUC of 0.58. CONCLUSION: XGBoost was used to predict 30-day readmission and reoperation for HN free flap patients. Findings may be used to assist clinicians and patients in shared decision-making and improve data collection in future database iterations.

Six-week postoperative opioid use and pain following a randomized controlled trial evaluating multimodal analgesia for head and neck free flap patients.

Introduction: Head and neck malignancy treatment often involves invasive surgeries, necessitating effective postoperative pain control. However, chronic reliance on opioid medications remains a challenge for many patients after surgery. Multimodal analgesia (MMA) within enhanced recovery after surgery protocols has shown success in limiting narcotic pain medications for other cancer types. In a prior study, MMA comprising acetaminophen, ketorolac, gabapentin, and a neurogenic block reduced opioid use in the 7-day postoperative period for major head and neck reconstructive surgery. This study investigates the impact of multimodal analgesia on opioid prescription and pain during the 6-week postoperative period for patients undergoing major head and neck oncologic surgeries, aiming to understand the longer-term effects of narcotic use. Methods: The study retrospectively examined participants in a [hybrid type 1 effectiveness-implementation pragmatic trial to assess multimodal analgesia's long-term effectiveness in head and neck free flap surgery. Arm A received scheduled acetaminophen and as-needed opioids, while Arm B received scheduled gabapentin, ketorolac, a regional nerve block at the donor site, scheduled acetaminophen, and as-needed opioids. Retrospective data collection included opioid prescription use and pain scores up to 6 weeks after surgery, gathered from the Kansas prescription drug monitoring program, K-TRACS. Results: Thirty patients participated, 14 in Arm A and 16 in Arm B. The average morphine milligram equivalents per day of filled prescriptions were not significantly different between Arm A and Arm B (7.23 vs. 7.88, p = .845). Additionally, average pain scores at 6 weeks showed no significant difference between the two groups (1.4 vs. 1.9, p = .612). Conclusion: Patients with head and neck cancer treated with multimodal analgesia during the perioperative period did not exhibit significant differences in opioid use and pain within 6 weeks after discharge. To confirm these findings, a re-examination with strict measures of opioid use and scheduled pain assessments in a prospective manner is warranted. Level of Evidence: 4.

Predicting Therapeutic Response to Hypoglossal Nerve Stimulation Using Deep Learning.

OBJECTIVES: To develop and validate machine learning (ML) and deep learning (DL) models using drug-induced sleep endoscopy (DISE) images to predict the therapeutic efficacy of hypoglossal nerve stimulator (HGNS) implantation. METHODS: Patients who underwent DISE and subsequent HGNS implantation at a tertiary care referral center were included. Six DL models and five ML algorithms were trained on images from the base of tongue (BOT) and velopharynx (VP) from patients classified as responders or non-responders as defined by Sher's criteria (50% reduction in apnea-hypopnea index (AHI) and AHI < 15 events/h). Precision, recall, F1 score, and overall accuracy were evaluated as measures of performance. RESULTS: In total, 25,040 images from 127 patients were included, of which 16,515 (69.3%) were from responders and 8,262 (30.7%) from non-responders. Models trained on the VP dataset had greater overall accuracy when compared to BOT alone and combined VP and BOT image sets, suggesting that VP images contain discriminative features for identifying therapeutic efficacy. The VCG-16 DL model had the best overall performance on the VP image set with high training accuracy (0.833), F1 score (0.78), and recall (0.883). Among ML models, the logistic regression model had the greatest accuracy (0.685) and F1 score (0.813). CONCLUSION: Deep neural networks have potential to predict HGNS therapeutic efficacy using images from DISE, facilitating better patient selection for implantation. Development of multi-institutional data and image sets will allow for development of generalizable predictive models. LEVEL OF EVIDENCE: N/A Laryngoscope, 2024.

Impact of Adjuvant Radiotherapy Setting on Quality-of-Life in Head and Neck Squamous Cell Carcinoma.

OBJECTIVE: To determine differences in post-treatment QoL across treatment settings in patients receiving adjuvant radiation therapy for head and neck squamous cell carcinoma (HNSCC). METHODS: This was a prospective observational cohort study of patients with HNSCC initially evaluated in a head and neck surgical oncologic and reconstructive clinic at an academic medical center (AMC). Participants were enrolled prior to treatment in a prospective registry collecting demographic, social, and clinical data. Physical and social-emotional QoL (phys-QoL and soc-QoL, respectively) was measured using the University of Washington-QoL questionnaire at pre-treatment and post-treatment visits. RESULTS: A cohort of 177 patients, primarily male and White with an average age of 61.2 ± 11.2 years, met inclusion criteria. Most patients presented with oral cavity tumors (n = 132, 74.6%), had non-HPV-mediated disease (n = 97, 61.8%), and were classified as Stage IVa (n = 72, 42.8%). After controlling for covariates, patients treated at community medical centers (CMCs) reported a 7.15-point lower phys-QoL compared with those treated at AMCs (95% CI: -13.96 to -0.35, p = 0.040) up to 12 months post-treatment. Additionally, patients who were treated at CMCs had a 5.77-point (-11.86-0.31, p = 0.063) lower soc-QoL score compared with those treated at an AMC, which was not statistically significant. CONCLUSION: This study revealed that HNSCC patients treated with radiation at AMCs reported significantly greater phys-QoL in their first-year post-treatment compared to those treated at CMCs, but soc-QoL did not differ significantly. Further observational studies are needed to explore potential factors, including treatment planning and cancer resource engagement, behind disparities between AMCs and CMCs. LEVEL OF EVIDENCE: Step 3 Laryngoscope, 2024.

Disentangling Social Determinants of Health and Rurality in Head and Neck Cancer 2-Year Mortality.

Social determinants of health (SDoH) and rurality are known factors that may influence outcomes in head and neck squamous cell carcinoma (HNSCC). Patients residing in remote locations or those with multiple SDoH may encounter barriers to initial diagnosis, adherence to multidisciplinary treatments, and posttreatment surveillance, which may impact their overall survival. However, previous studies have shown mixed results associated with rural residence. The aim of this study is to identify the impact of rurality and SDoH on 2-year survival in HNSCC. The study was conducted using a Head and Neck Cancer Registry at a single institution from June 2018 through July 2022. Rurality, defined by US census scores, and individual measures of SDoH were used. Our results indicate that each additional adverse SDoH factor results in 1.5 times the odds of mortality at 2 years. Individualized measures of SDoH, rather than rurality alone, better reflect patient prognosis in HNSCC.

Preoperative Examination Is Not Associated with Postoperative Function following Radial Forearm Free Flap Harvest.

BACKGROUND: There is debate on the utility of a preoperative Allen test or ultrasound before radial forearm free flap (RFFF) harvest. This study sought to evaluate correlations between preoperative testing and donor-site morbidity. METHODS: A survey of plastic surgery and otolaryngology RFFF patients was conducted at a Midwestern academic center. The modified Cold Intolerance Symptom Severity (modCISS) and Quick Disabilities of the Arm, Shoulder, and Hand (QDASH) instruments were administered. A retrospective chart review was performed to assess perioperative factors. RESULTS: Of 212 RFFFs completed over 7 years, 144 patients were contacted, and 71 patients completed the survey (33% response rate). Preoperative Allen test was negative in 92% of patients (65 of 71). There was no statistical association between Allen test and duplex ultrasound findings ( P = 0.19). Cold intolerance screening was positive on 20% of donor arms (14 of 71), with an average positive modCISS score of 39.0 ± 14.7. Disability was reported on the QDASH by 76% of patients (54 of 71), with an average score of 21.0 ± 22.3. There was no statistical correlation between preoperative Allen test or ultrasound classification and modCISS or QDASH score. There was a borderline positive correlation between modCISS and QDASH scores that did not reach statistical significance ( r = 0.22, P = 0.067). Operative characteristics also did not predict modCISS or QDASH scores. CONCLUSIONS: Following RFFF harvest, donor extremity cold intolerance is reported in 20% of patients, and extremity-related disability is reported in the majority of patients. Preoperative ultrasound and physical examination findings are not predictive of morbidity.

The Use of Dissemination and Implementation to Improve Multimodal Analgesia in Head and Neck Surgery.

OBJECTIVES: To optimize the delivery of multimodal analgesia to patients undergoing major head and neck oncologic surgeries. METHODS: Pilot study included patients enrolled to receive either scheduled acetaminophen and as-needed opioids (control group) or scheduled acetaminophen, gabapentin, ketorolac, and as-needed opioids (experimental group). RCT, a hybrid type 1 effectiveness-implementation pragmatic trial, was designed to test the effectiveness of the intervention. Arm A received scheduled acetaminophen and as-needed opioids. Arm B received scheduled gabapentin, ketorolac, a regional nerve block at the free tissue donor site, scheduled acetaminophen and as-needed opioids. RESULTS: Pilot: Thirty-one patients undergoing major head and neck surgery were enrolled. Mean MMEs administered in control group (n = 15) was 251.60 mg (SD = 224.57 mg); mean MMEs in Experimental group (n = 16) was 195.78 mg (SD = 131.08 mg), p = 0.401. LOS was 8.0 days in control versus 7.0 days in experimental group (p = 0.054). RCT: Interim analysis for safety and futility was planned during trial's design after 30 patients (n = 14 Arm A, and n = 16 Arm B). Mean MMEs administered were 135.1 mg in Arm A, (SD = 86.0 mg) versus mean MME of 51.3 mg in Arm B (SD = 43.3 mg, (p < 0.05)). Given clear superiority results, the trial was prematurely terminated. Functional pain scores, LOS, and complications were similar between the arms (p > 0.05). Variability of mean MME was compared before and after implementation of the management protocols: SD in RCT#1 was 181.46 mg versus 124.6 mg in RCT#2. CONCLUSION: Multimodal analgesia significantly reduced the need for opioids in patients undergoing major head and neck surgery. LEVEL OF EVIDENCE: 1, Randomized Clinical Trial Laryngoscope, 133:S1-S11, 2023.

Gender, Smoking History, and Age Prediction from Laryngeal Images.

Flexible laryngoscopy is commonly performed by otolaryngologists to detect laryngeal diseases and to recognize potentially malignant lesions. Recently, researchers have introduced machine learning techniques to facilitate automated diagnosis using laryngeal images and achieved promising results. The diagnostic performance can be improved when patients' demographic information is incorporated into models. However, the manual entry of patient data is time-consuming for clinicians. In this study, we made the first endeavor to employ deep learning models to predict patient demographic information to improve the detector model's performance. The overall accuracy for gender, smoking history, and age was 85.5%, 65.2%, and 75.9%, respectively. We also created a new laryngoscopic image set for the machine learning study and benchmarked the performance of eight classical deep learning models based on CNNs and Transformers. The results can be integrated into current learning models to improve their performance by incorporating the patient's demographic information.

Interpretable Computer Vision to Detect and Classify Structural Laryngeal Lesions in Digital Flexible Laryngoscopic Images.

OBJECTIVE: To localize structural laryngeal lesions within digital flexible laryngoscopic images and to classify them as benign or suspicious for malignancy using state-of-the-art computer vision detection models. STUDY DESIGN: Cross-sectional diagnostic study SETTING: Tertiary care voice clinic METHODS: Digital stroboscopic videos, demographic and clinical data were collected from patients evaluated for a structural laryngeal lesion. Laryngoscopic images were extracted from videos and manually labeled with bounding boxes encompassing the lesion. Four detection models were employed to simultaneously localize and classify structural laryngeal lesions in laryngoscopic images. Classification accuracy, intersection over union (IoU) and mean average precision (mAP) were evaluated as measures of classification, localization, and overall performance, respectively. RESULTS: In total, 8,172 images from 147 patients were included in the laryngeal image dataset. Classification accuracy was 88.5 for individual laryngeal images and increased to 92.0 when all images belonging to the same sequence (video) were considered. Mean average precision across all four detection models was 50.1 using an IoU threshold of 0.5 to determine successful localization. CONCLUSION: Results of this study showed that deep neural network-based detection models trained using a labeled dataset of digital laryngeal images have the potential to classify structural laryngeal lesions as benign or suspicious for malignancy and to localize them within an image. This approach provides valuable insight into which part of the image was used by the model to determine a diagnosis, allowing clinicians to independently evaluate models' predictions.

Pilot randomized, controlled, preoperative intervention for nutrition trial in head and neck cancer.

BACKGROUND: Several prospective studies report improved outcomes with pretreatment nutrition interventions prior to radiation therapy for head and neck cancer (HNC), but none have assessed similar interventions before surgery for HNC. METHODS: POINT, a pilot randomized controlled trial, was conducted to evaluate a multimodal nutrition intervention. Patients undergoing primary surgery with free flap reconstruction for HNC were randomly assigned to the control arm or a preoperative multimodal nutrition intervention. RESULTS: POINT included 49 patients. Nutrition risk scores did not change significantly for either the intervention or control group. Control patients had a significant decrease in body weight in the preoperative period (p < 0.001). Conversely, weight among intervention patients did not significantly decrease (p = 0.680). The intervention mitigated weight loss in patients with dysphagia (p = 0.001). CONCLUSIONS: Preoperative nutrition optimization shows potential to reduce weight loss normally experienced by patients with head and neck cancer prior to surgical extirpation, especially among those with subjective dysphagia.

Prognostic Implications of Skin Invasion in Locally Advanced Oral Cavity Squamous Cell Carcinoma.

OBJECTIVE: To evaluate the effect of histopathologic skin invasion on 2- and 5-year disease-free survival (DFS) and overall survival (OS) in patients treated with primary surgery for locally advanced oral cavity squamous cell carcinoma (OCSCC). STUDY DESIGN: A retrospective case-control study was performed comparing previously untreated patients with pT4a OCSCC with and without skin invasion. SETTING: Academic medical center. METHODS: Propensity score-matched cohorts were derived by age, sex, surgical margins, pathologic N classification, adjuvant treatment, and primary tumor site. The Kaplan-Meier method was used to evaluate 2- and 5-year OS and DFS, which were compared between cohorts via the log rank (Mantel-Cox) test statistic. RESULTS: Overall 25 patients were identified to have pathologic skin invasion, and 50 were selected for the matched control group. OS was significantly lower for patients with skin invasion as compared with controls at 2 years (30.8% vs 53.3%, P = .018) and 5 years (16.6% vs 42.2%, P = .01). DFS was significantly lower for patients with skin invasion vs controls at 2 years (23.7% vs 47.7, P = .037) and 5 years (15.8% vs 41.4%, P = .024). CONCLUSION: Histopathologic skin invasion in OCSCC is associated with dismal prognosis in patients who underwent primary surgical treatment. OS outcomes for patients with skin invasion are comparable to survival of patients with recurrent/metastatic disease and T4N2 disease.

Assessing the Risk of Adjuvant Radiotherapy Initiation Delays With Social Support Surveys.

OBJECTIVE: In patients with head and neck squamous cell carcinoma (HNSCC), initiating postoperative radiotherapy (PORT) greater than 42 days after surgery is associated with a higher risk of poor survival outcomes. Social support has been shown to modulate behaviors related to care-seeking and treatment adherence. In this study, we sought to determine the relationship between social support metrics and PORT delays. STUDY DESIGN: Prospective cohort study. SETTING: Single tertiary medical center. METHODS: Patients with HNSCC who underwent primary surgical excision requiring PORT were prospectively enrolled. Patient-perceived social support metrics were assessed using the Medical Outcomes Study Social Support Survey (MOS-SSS) at initial presurgical evaluation. Associations with PORT delays were evaluated via univariable and multivariable logistic regression analysis. RESULTS: A total of 111 patients met the inclusion criteria for the study. An additional 28 patients were recommended to receive PORT but did not initiate treatment and were included for secondary analysis. All four subscales of the MOS-SSS (positive social interaction, affectionate support, tangible support, and emotional/informational support) were significantly associated with PORT initiation delays on univariable analysis. On multivariable analysis, the overall MOS-SSS score (odds ratio [OR] 2.08, 1.15-4.35, p = .028) was significantly associated with PORT initiation delays. On secondary analysis, lower tangible support was associated with a lack of PORT initiation (OR 1.63, 1.05-2.54, p = .028). CONCLUSION: Social support metrics were significantly associated with PORT delays, which may help promote tighter scheduling and closer monitoring of high-risk patients.

Association of Social-Ecological Factors With Delay in Time to Initiation of Postoperative Radiation Therapy: A Prospective Cohort Study.

Importance: Timely initiation of postoperative radiation therapy (PORT) is associated with reduced recurrence rates and improved overall survival in patients with head and neck squamous cell carcinoma (HNSCC). Measurement of the association of social-ecological variables with PORT delays is lacking. Objective: To assess individual and community-level factors associated with PORT delay among patients with HNSCC. Design, Setting, and Participants: This prospective cohort study carried out between September 2018 and June 2022 included adults with untreated HNSCC who were enrolled in a prospective registry at a single academic tertiary medical center. Demographic information and validated self-reported measures of health literacy were obtained at baseline visits. Clinical data were recorded, and participant addresses were used to calculate the area deprivation index (ADI), a measure of community-level social vulnerability. Participants receiving primary surgery and PORT were analyzed. Univariable and multivariable regression analysis was performed to identify risk factors for PORT delays. Exposures: Surgical treatment and PORT. Main Outcomes and Measures: The primary outcome was PORT initiation delay (>42 days from surgery). Risk of PORT initiation delay was evaluated using individual-level (demographic, health literacy, and clinical data) and community-level information (ADI and rural-urban continuum codes). Results: Of 171 patients, 104 patients (60.8%) had PORT delays. Mean (SD) age of participants was 61.0 (11.2) years, 161 were White (94.2%), and 105 were men (61.4%). Insurance was employer-based or public among 65 (38.5%) and 75 (44.4%) participants, respectively. Mean (SD) ADI (national percentile) was 60.2 (24.4), and 71 (41.8%) resided in rural communities. Tumor sites were most commonly oral cavity (123 [71.9%]), with 108 (63.5%) classified as stage 4 at presentation. On multivariable analysis, a model incorporating individual-level factors with health literacy in addition to community-level factors was most predictive of PORT delay (AOC= 0.78; R2, 0.18). Conclusions and Relevance: This cohort study provides a more comprehensive assessment of predictors of PORT delays that include health literacy and community-level measures. Predictive models that incorporate multilevel measures outperform models with individual-level factors alone and may guide precise interventions to decrease PORT delay for at-risk patients with HNSCC.