The impact of the oral microbiome on head and neck cancer pathogenesis and outcomes requires further study. 16s rRNA was isolated and amplified from pre-treatment oral wash samples for 52 cases and 102 controls. The sequences were binned into operational taxonomic units (OTUs) at the genus level. Diversity metrics and significant associations between OTUs and case status were assessed. The samples were binned into community types using Dirichlet multinomial models, and survival outcomes were assessed by community type. Twelve OTUs from the phyla Firmicutes, Proteobacteria, and Acinetobacter were found to differ significantly between the cases and the controls. Beta-diversity was significantly higher between the cases than between the controls (p < 0.01). Two community types were identified based on the predominant sets of OTUs within our study population. The community type with a higher abundance of periodontitis-associated bacteria was more likely to be present in the cases (p < 0.01), in older patients (p < 0.01), and in smokers (p < 0.01). Significant differences between the cases and the controls in community type, beta-diversity, and OTUs indicate that the oral microbiome may play a role in HNSCC.

Purpose: Although ctDNA is a promising biomarker for minimal residual disease (MRD) detection in head and neck squamous cell carcinoma (HNSCC), more sensitive assays are needed for accurate MRD detection at clinically relevant time points. Ultrasensitive MRD detection early after surgery could guide adjuvant therapy decisions, but early ctDNA dynamics are poorly understood. Experimental Design: We applied minor allele–enriched sequencing through recognition oligonucleotides (MAESTRO), a whole-genome, tumor-informed, mutation enrichment sequencing assay, in a pooled testing format called MAESTRO-Pool, to plasma samples from patients with HNSCC collected shortly after surgery and during surveillance. We evaluated whether early MRD detection could predict outcomes. Results: Among 24 patients with predominantly human papillomavirus–independent (95.8%) HNSCC, rapid ctDNA clearance occurred by the first postoperative sample (1–3 days postoperatively) in nine patients without an event (recurrence or death). Thirteen of fifteen patients with an event were MRD-positive (positive predictive value = 92.9%; negative predictive value = 80%) with a median tumor fraction (TFx) of 54 parts per million (ppm; range 6–1,177 ppm). In the first and last samples of the early postoperative window, 8/13 and 10/13 patients, respectively, had TFx below 100 ppm, the detection limit of leading commercial assays. Early MRD detection correlated with worse overall survival (HR, 8.3; 95% confidence interval, 1.1–66.1; P = 0.02) and event-free survival (HR, 27.4; 95% confidence interval, 3.5–214.5; P < 0.0001) independent of high-risk pathology. Conclusions: Early postoperative MRD detection by MAESTRO was associated with recurrence and worse survival. Given the ultralow TFxs observed, ultrasensitive assays will be essential for reliable MRD detection during early postoperative time points to enable personalized adjuvant therapy decision-making in HNSCC. See related article by Bryan et al., p. XX .

Purpose To assess the impact of applicant and residency program characteristics on preference signaling outcomes in the Match during the first 2 years of implementation across 6 specialties. Method Data were obtained from the Texas Seeking Transparency in Application to Residency survey for applicants applying into otolaryngology during the 2020–2021 and 2021–2022 application cycles and into dermatology, internal medicine (categorical and preliminary year), general surgery, and urology during the 2021–2022 application cycle. The primary outcome was signal yield, defined as the number of interviews at signaled programs divided by the total number of signals sent. Associations with applicant-reported characteristics and geographic connections to residency programs were assessed using Wilcoxon rank sum testing, Spearman’s rank correlation testing, and ordinary least squares regression. Results 1,749 applicants with preference signaling data were included from internal medicine (n = 884), general surgery (n = 291), otolaryngology (n = 217), dermatology (n = 147), urology (n = 124), and internal medicine preliminary year (n = 86). On average 60.9% (standard deviation 32.3%) of signals resulted in an interview (signal yield). There was a stepwise increase in signal yield with the percentage of signals sent to programs with a geographic connection (57.3% for no signals vs. 68.9% for 5 signals, P < .01). Signal yield was positively associated with applicant characteristics, such as United States Medical Licensing Exam Step 1 and 2 scores, honors society membership, and number of publications (P < .01). Applicants reporting a lower class rank quartile were significantly more likely to have a higher percentage of their interviews come from signaled programs (P < .01). Conclusions Signal yield is significantly associated with geographic connections to residency programs and applicant competitiveness based on traditional metrics. These findings can inform applicants, programs, and specialties as preference signaling grows.

Objective: This study aims to assess trends in applicant‐reported costs of the otolaryngology residency application process between 2019 and 2021 and evaluate the impact of application costs on number of interview offers.Study Design: Cross‐sectional study.Setting: US allopathic and osteopathic medical schools.Methods: Survey data from applicants were obtained from the Texas STAR database (Seeking Transparency in Application to Residency) for the years 2019 to 2021. Outcomes included total cost, interview cost, other costs, application fees, and number of interview offers. Simple and multivariable linear regression was used to identify novel predictors of cost and assess the correlation between cost and interview offers.Results: Among 363 otolaryngology applicants, there was a 74% reduction in total costs and a 97% reduction in interview costs in the 2021 cycle vs the 2020 cycle. Significant predictors of total cost among otolaryngology applicants included the number of away rotations (P <. 01), the number of research experiences (P =. 04), and couples matching (P <. 01). During the 2019 and 2020 application cycles, there was a significant association between applicant‐reported total spending and number of otolaryngology interview offers (P <. 01), which was not present during the 2021 cycle (P =. 35).Conclusion: Number of otolaryngology interview offers appears to be directly correlated with applicant‐reported total costs regardless of number of applications or interviews attended, which may be a source of inequality in the application process. There was a drastic reduction in total costs, interview costs, and other costs during the COVID‐19 pandemic, which was likely driven by virtual interviewing and the absence of away rotations.

Objectives: To assess the impact of applicant and program characteristics on preference signaling outcomes during the 2021 and 2022 application cycles in otolaryngology.Methods: The Texas Seeking Transparency in Applications to Residency survey was used for otolaryngology applicants during the 2021 and 2022 match years. The primary outcome of interest was signal yield, defined as the number of interviews at signaled programs divided by the total number of signals sent. Associations with applicant‐reported characteristics, geographic connections to programs, and program reputation were assessed.Results: On average 59.5% of signals resulted in an interview (signal yield). There was a positive correlation between the number of signals sent to a program with a reported geographic connection and signal yield, with each additional signal resulting in a 3.4% increase in signal yield (p = .03). Signal yield was positively associated with number of publications (p < .001); number of abstracts, posters, and presentations (p = .04); and whether the applicant took a research year (p = .003). Applicants with higher USMLE Step 1 (p = .01) and Step 2 (p = .003) scores, publications (p = .03), volunteer (p = .008) and leadership (p = .001) experiences received a lower percentage of their total interviews from signaled programs whereas applicants from the 3rd (p < .001) and 4th (p = .03) cumulative class ranked quartiles received a higher percentage of their total interviews from signaled programs.Conclusions: Signal yield appears to have a significant association with geographic connections to programs and applicant competitiveness. This study may help applicants, advisors, and programs maximize the benefit of the preference signaling system.Levels of evidence: Level 4.