Characterisation of delayed severity flares in patients with HLA-B27-associated anterior uveitis.

BACKGROUND/AIMS: To explore and characterise the clinical phenotype of acute anterior uveitis flares with delayed severity in patients with human leucocyte antigen B27 (HLA-B27)-associated anterior uveitis. METHODS: Retrospective chart review of patients with HLA-B27-associated anterior uveitis. Demographic and clinical data were recorded, as well as the clinical characteristics of acute anterior uveitis flares. A flare was considered to have delayed severity if any of the following criteria were met within 3-21 days of symptomatic onset: a two-step increase in anterior chamber inflammation on consecutive exams; a new development of hypopyon or fibrinoid aqueous reaction on consecutive examinations or a significant worsening of symptoms. RESULTS: A total of 371 patient charts were identified, of which 137 were included. 321 acute anterior uveitis flares were documented, with 36 (11.2%) meeting the criteria for a delayed severity flare. The average time from symptomatic onset was 10.2 days, and patients presented with an average anterior chamber cell grade of 3.5 in delayed severity flares compared with 1.6 in non-delayed severity flares. No significant difference in frequency of delayed severity presentation was noted based on the presence or absence of systemically associated rheumatological disease, papillitis on initial presentation and retinal vasculitis on initial presentation. The frequency of topical steroid therapy after symptomatic onset was not significantly different between the two flare phenotypes. CONCLUSIONS: Our study presents the novel characterisation of a delayed severity phenotype of HLA-B27-associated acute anterior uveitis flares.

Characterization of mavacamten pharmacokinetics in patients with hypertrophic cardiomyopathy to inform dose titration.

Mavacamten is a selective, allosteric, reversible cardiac myosin inhibitor that has been developed for the treatment of adults with symptomatic obstructive hypertrophic cardiomyopathy (HCM). A population pharmacokinetic (PopPK) model was developed to characterize mavacamten pharmacokinetics (PK) and the variation in mavacamten exposure associated with intrinsic and extrinsic factors. Data from 12 clinical studies (phases 1, 2, and 3) were used. Evaluable participants were those who had at least one mavacamten concentration measurement with associated sampling time and dosing information. The base model included key covariates: body weight, cytochrome P450 isozyme 2C19 (CYP2C19) phenotype with respect to PK, and formulation. The final model was generated using stepwise covariate testing and refinement processes. Simulations were performed to evaluate PK: apparent clearance (CL/F); apparent central and peripheral volumes of distribution; and steady-state average, trough, and maximum concentrations. Overall, 9244 measurable PK observations from 497 participants were included. A two-compartment model structure was selected. After stepwise covariate model building and refinement, additional covariates included were: specified mavacamten dose, omeprazole or esomeprazole administration, health/disease status, estimated glomerular filtration rate, fed status, and sex. The final PopPK model accurately characterized mavacamten concentrations. At any given dose, CYP2C19 phenotype was the most influential covariate on exposure parameters (e.g., median CL/F was reduced by 72% in CYP2C19:poor metabolizers compared with the reference participant [CYP2C19:normal metabolizer]). CL/F was also approximately 16% higher in women than in men but lower in participants receiving concomitant omeprazole or esomeprazole (by 33% and 42%, respectively) than in participants not receiving such concomitant therapy.

Performance and clinical utility of an artificial intelligence-enabled tool for pulmonary embolism detection.

PURPOSE: Diagnosing pulmonary embolism (PE) is still challenging due to other conditions that can mimic its appearance, leading to incomplete or delayed management and several inter-observer variabilities. This study evaluated the performance and clinical utility of an artificial intelligence (AI)-based application designed to assist clinicians in the detection of PE on CT pulmonary angiography (CTPA). PATIENTS AND METHODS: CTPAs from 230 US cities acquired on 57 scanner models from 6 different vendors were retrospectively collected. Three US board certified expert radiologists defined the ground truth by majority agreement. The same cases were analyzed by CINA-PE, an AI-driven algorithm capable of detecting and highlighting suspected PE locations. The algorithm's performance at a per-case and per-finding level was evaluated. Furthermore, cases with PE not mentioned in the clinical report but correctly detected by the algorithm were analyzed. RESULTS: A total of 1204 CTPAs (mean age 62.1 years ± 16.6[SD], 44.4 % female, 14.9 % positive) were included in the study. Per-case sensitivity and specificity were 93.9 % (95%CI: 89.3 %-96.9 %) and 94.8 % (95%CI: 93.3 %-96.1 %), respectively. Per-finding positive predictive value was 89.5 % (95%CI: 86.7 %-91.9 %). Among the 196 positive cases, 29 (15.6 %) were not mentioned in the clinical report. The algorithm detected 22/29 (76 %) of these cases, leading to a reduction in the miss rate from 15.6 % to 3.8 % (7/186). CONCLUSIONS: The AI-based application may improve diagnostic accuracy in detecting PE and enhance patient outcomes through timely intervention. Integrating AI tools in clinical workflows can reduce missed or delayed diagnoses, and positively impact healthcare delivery and patient care.

Fertility in the Digital Age: A Survey-Based Evaluation of Fertility App Users' Quality of Life.

This study sought to characterize fertility app use among women seen for infertility care and to investigate the association between fertility app use and quality of life. This survey-based study was conducted at an academic infertility clinic. Surveys were administered to patients who presented for a new infertility visit. One survey collected information regarding app use and the second survey was FertiQoL, an internationally validated instrument measuring quality of life in those with infertility. Descriptive statistics were used to characterize the patient population regarding app use and FertiQoL scores. Comparisons between those who did and didn't use an app were evaluated using t-tests and Cochran Armitage test for trend. 149 surveys were collected. Most (75.5%) participants reported using a fertility app. Most participants (85.1%) used a free app and nearly all (97.2%) found their app helpful. There was a significant difference (p = 0.0034) in satisfaction with one's quality of life between app users and non-app users with app users demonstrating higher satisfaction. There were no significant differences between app users and non-app users with their overall FertiQoL scores however there was a statistically significant difference (p = 0.031) in Relational sub-scores with app users displaying higher scores. While overall quality of life, measured by standardized measures, did not differ, self-perceived satisfaction with quality of life improved with more satisfaction reported in those using an app. This self-perceived satisfaction and increased quality of life surrounding relationships carries important implications, especially when one may face the stress of infertility and its treatment.

Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts.

The Radiological Society of North of America (RSNA) and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society have led a series of joint panels and seminars focused on the present impact and future directions of artificial intelligence (AI) in radiology. These conversations have collected viewpoints from multidisciplinary experts in radiology, medical imaging, and machine learning on the current clinical penetration of AI technology in radiology and how it is impacted by trust, reproducibility, explainability, and accountability. The collective points-both practical and philosophical-define the cultural changes for radiologists and AI scientists working together and describe the challenges ahead for AI technologies to meet broad approval. This article presents the perspectives of experts from MICCAI and RSNA on the clinical, cultural, computational, and regulatory considerations-coupled with recommended reading materials-essential to adopt AI technology successfully in radiology and, more generally, in clinical practice. The report emphasizes the importance of collaboration to improve clinical deployment, highlights the need to integrate clinical and medical imaging data, and introduces strategies to ensure smooth and incentivized integration. Keywords: Adults and Pediatrics, Computer Applications-General (Informatics), Diagnosis, Prognosis © RSNA, 2024.

Histopathology imaging and clinical data including remission status in pediatric inflammatory bowel disease.

The incidence of inflammatory bowel disease (IBD) is increasing annually. Children with IBD often suffer significant morbidity due to physical and emotional effects of the disease and treatment. Corticosteroids, often a component of therapy, carry undesirable side effects with long term use. Steroid-free remission has become a standard for care-quality improvement. Anticipating therapeutic outcomes is difficult, with treatments often leveraged in a trial-and-error fashion. Artificial intelligence (AI) has demonstrated success in medical imaging classification tasks. Predicting patients who will attain remission will help inform treatment decisions. The provided dataset comprises 951 tissue section scans (167 whole-slides) obtained from 18 pediatric IBD patients. Patient level structured data include IBD diagnosis, 12- and 52-week steroid use and name, and remission status. Each slide is labelled with biopsy site and normal or abnormal classification per the surgical pathology report. Each tissue section scan from an abnormal slide is further classified by an experienced pathologist. Researchers utilizing this dataset may select from the provided outcomes or add labels and annotations from their own institutions.

Arthroscopic rotator cuff repair in active patients younger than 45 Years: a prospective analysis with a mean 5-year follow-up.

Background: To report clinical and activity-specific outcomes after arthroscopic rotator cuff repair (ARCR) for full-thickness supraspinatus tears in active individuals aged less than or equal to 45 years. The pre hoc hypothesis was that patients in this age group would demonstrate significant improvements in clinical outcomes following ARCR along with a significant improvement of athletic abilities. Methods: Patients were included in this study if they were (1) active individuals aged between 18 and 45 years at the time of surgery, (2) had a full-thickness rotator cuff tear of the supraspinatus tendon with or without anterior or posterior extension, and (3) underwent ARCR. Preoperative and postoperative patient-reported outcomes scores including the American Shoulder and Elbow Surgeons (ASES) score; Disabilities of Arm, Shoulder and Hand; Single Assessment Numeric Evaluation; and Short Form-12 Physical Component Summary were prospectively collected and postoperative patient satisfaction (scale of 1-10) was recorded at a minimum of 2 years postoperatively. Attainment of the minimal clinically important difference and patient acceptable symptom state for the ASES was calculated. Athletic activity-specific outcomes and return to activity were investigated prospectively via a custom-made comprehensive questionnaire. Results: Between November 2005 and June 2020, of 1149 RCRs performed by the senior author, 54 patients (mean age 40.9 years, 13 female; follow-up 69.7 ± 35.2 months in a range of 24.6-179.6 months) were included into the outcomes analysis. Of those, 4 patients (7.4%) had progressed to revision RCR. At a follow-up of 5.8 years, outcome scores had significantly improved compared to preoperative baselines (ASES 55.6 ± 13.8 to 90.1 + 15.8; P < .001; Disabilities of Arm, Shoulder and Hand 38.9 ± 18.4 to 11.9 ± 17.1; P < .001, Single Assessment Numeric Evaluation 60.7 ± 22.7 to 79.3 ± 27.6; P = .001, Short Form-12 Physical Component Summary 41.6 ± 8.3 to 51.9 ± 9.0; P ≤ .001). Ninety three point six percent of the patients reached the minimal clinically important difference and 72.6% reached the patient acceptable symptom state. Median satisfaction was 9.5/10. Eighty six percent of the patients returned to sports, while 67% of the patients returned to a similar level compared to preoperatively. All sport-specific metrics such as shoulder strength and endurance (P < .001), intensity (P < .001), and impairments from pain affecting speed (P = .002), endurance (P = .002), and competition (P < .001) significantly improved postoperatively. Conclusion: ARCR of full-thickness rotator cuff tear in active individuals aged 45 years or less results in a clinically relevant improvement of outcomes, function, and quality of life at a minimum of 2 years and mean 5.8-year follow-up with a low rate of revision. While 86% of patients were able to return to activity and sport-specific outcome metrics significantly and substantially improved compared to preoperatively, a return to preinjury levels was not reliably achieved in all patients, with particular limitations observed in overhead active individuals. The data support the hypothesis that patients in this age group demonstrate significant improvements in clinical outcomes following ARCR along with significant improvements in athletic abilities.

Paclitaxel-Ifosfamide-based Therapy as Salvage Treatment in Platinum-resistant Recurrent/Metastatic Head and Neck Cancer.

BACKGROUND: Treatment options are limited, and the prognosis is poor for patients with platinum-resistant recurrent metastatic (R/M) head and neck squamous cell carcinoma (HNSCC). This study evaluated the efficacy and safety of a paclitaxel and ifosfamide (TI) regimen in patients with R/M HNSCC whose disease had progressed following platinum-based therapy. PATIENTS AND METHODS: In this retrospective study, we included 53 patients with R/M HNSCC who underwent at least one cycle of TI-based therapy, post platinum failure, between February 2020 and August 2023. Some patients received the TI regimen in combination with immunotherapy and/or cetuximab. Key metrics assessed included the objective response rate (ORR), disease control rate, and progression-free as well as overall survival. RESULTS: The study observed an ORR of 15.8% and a disease control rate of 36.8%. The median progression-free survival for the entire cohort was 3.3 months, and the median overall survival was 9.6 months. Notably, the combination of TI with immunotherapy yielded a higher ORR of 30.8%, compared to 14.3% with TI alone. The most prevalent grade 1-2 adverse events were anemia (81%), weight loss (68%) and hypernatremia (55%). CONCLUSION: The TI-based regimen demonstrated favorable efficacy and safety profile in treating R/M HNSCC. Enhanced outcomes may be attainable when combining it with immunotherapy. This study suggests that TI-based therapy could serve as a potential salvage option for this specific patient group.

AI Efficacy as a Function of Trainee Interpreter Proficiency: Lessons from a Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Recently, AI tools have been deployed with increasing speed in educational and clinical settings. However, the use of AI by trainees across different levels of experience has not been well studied. This study investigates the impact of AI assistance on diagnostic accuracy for intracranial hemorrhage (ICH) and large vessel occlusion (LVO) by medical students (MS) and resident trainees (RT). MATERIALS AND METHODS: This prospective study was conducted between March 2023 and October 2023. MS and RT were asked to identify ICH and LVO in 100 non-contrast head CTs and 100 head CTAs, respectively. One group received diagnostic aid simulating AI for ICH only (n = 26), the other for LVO only (n = 28). Primary outcomes included accuracy, sensitivity, and specificity for ICH / LVO detection without and with aid. Study interpretation time was a secondary outcome. Individual responses were pooled and analyzed with chi-square; differences in continuous variables were assessed with ANOVA. RESULTS: 48 participants completed the study, generating 10,779 ICH or LVO interpretations. With diagnostic aid, MS accuracy improved 11.0 points (P < .001) and RT accuracy showed no significant change. ICH interpretation time increased with diagnostic aid for both groups (P < .001) while LVO interpretation time decreased for MS (P < .001). Despite worse performance in detection of the smallest vs. the largest hemorrhages at baseline, MS were not more likely to accept a true positive AI result for these more difficult tasks. Both groups were considerably less accurate when disagreeing with the AI or when supplied with an incorrect AI result. CONCLUSIONS: This study demonstrated greater improvement in diagnostic accuracy with AI for MS compared to RT. However, MS were less likely than RT to overrule incorrect AI interpretations and were less accurate, even with diagnostic aid, than the AI was by itself. ABBREVIATIONS: ICH = intracranial hemorrhage; LVO = large vessel occlusion; MS = medical students; RT = resident trainees.

A novel IKZF1 variant in a family with autosomal dominant CVID: A case for expanding exon coverage in inborn errors of immunity.

Common variable immune deficiency (CVID) is a heterogenous group of disorders characterized by varying degrees of hypogammaglobulinemia, recurrent infections, and autoimmunity. Currently, pathogenic variants are identified in approximately 20-30% of CVID cases. Here we report a 3-generation family with autosomal dominant Common Variable Immunodeficiency (CVID) diagnosed in 9 affected individuals. Although primary immune deficiency panels and exome sequencing were non-diagnostic, whole genome sequencing revealed a novel, pathogenic c.499C > T: p.His167Tyr variant in IKZF1, a critical regulator of B cell development. Functional testing done through pericentromeric heterochromatin localization and light shift chemiluminescent electrophoretic mobility shift assay confirmed the variant's deleterious effect via a haploinsufficiency mechanism. Our findings expand the spectrum of known IKZF1 mutations and contribute to a more comprehensive understanding of CVID's genetic heterogeneity. Furthermore, this case underscores the importance of considering whole genome sequencing for comprehensive genetic diagnosis when concern for a monogenic inborn errors of immunity is high.

Population Pharmacokinetics of Sacituzumab Govitecan in Patients with Metastatic Triple-Negative Breast Cancer and Other Solid Tumors.

BACKGROUND AND OBJECTIVE: Sacituzumab govitecan (SG) is an antibody-drug conjugate composed of an antibody with affinity for Trop-2 coupled to SN-38 via hydrolyzable linker. SG is approved for patients with metastatic triple-negative breast cancer (mTNBC) who have received two or more prior chemotherapies (at least one in a metastatic setting) and for patients with pretreated hormone receptor positive (HR+)/human epidermal growth factor receptor 2 negative (HER2-) metastatic breast cancer. METHODS: In these analyses, the pharmacokinetics of SG, free SN-38, and total antibody (tAB) were characterized using data from 529 patients with mTNBC or other solid tumors across two large clinical trials (NCT01631552; ASCENT, NCT02574455). Three population pharmacokinetic models were constructed using non-linear mixed-effects modeling; clinically relevant covariates were evaluated to assess their impact on exposure. Models for SG and tAB were developed independently whereas free SN-38 was sequentially generated via a first-order release process from SG. RESULTS: Pharmacokinetics of the three analytes were each described by a two-compartment model with estimated body weight-based scaling exponents for clearance and volume. Typical parameter estimates for clearance and steady-state volume of distribution were 0.133 L/h and 3.68 L for SG and 0.0164 L/h and 4.26 L for tAB, respectively. Mild-to-moderate renal impairment, mild hepatic impairment, age, sex, baseline albumin level, tumor type, UGT1A1 genotype, or Trop-2 expression did not have a clinically relevant impact on exposure for any of the three analytes. CONCLUSIONS: These analyses support the approved SG dosing regimen of 10 mg/kg as intravenous infusion on days 1 and 8 of 21-day cycles and did not identify a need for dose adjustment based on evaluated covariates or disease characteristics.

Assessing the Performance of Artificial Intelligence Models: Insights from the American Society of Functional Neuroradiology Artificial Intelligence Competition.

BACKGROUND AND PURPOSE: Artificial intelligence models in radiology are frequently developed and validated using data sets from a single institution and are rarely tested on independent, external data sets, raising questions about their generalizability and applicability in clinical practice. The American Society of Functional Neuroradiology (ASFNR) organized a multicenter artificial intelligence competition to evaluate the proficiency of developed models in identifying various pathologies on NCCT, assessing age-based normality and estimating medical urgency. MATERIALS AND METHODS: In total, 1201 anonymized, full-head NCCT clinical scans from 5 institutions were pooled to form the data set. The data set encompassed studies with normal findings as well as those with pathologies, including acute ischemic stroke, intracranial hemorrhage, traumatic brain injury, and mass effect (detection of these, task 1). NCCTs were also assessed to determine if findings were consistent with expected brain changes for the patient's age (task 2: age-based normality assessment) and to identify any abnormalities requiring immediate medical attention (task 3: evaluation of findings for urgent intervention). Five neuroradiologists labeled each NCCT, with consensus interpretations serving as the ground truth. The competition was announced online, inviting academic institutions and companies. Independent central analysis assessed the performance of each model. Accuracy, sensitivity, specificity, positive and negative predictive values, and receiver operating characteristic (ROC) curves were generated for each artificial intelligence model, along with the area under the ROC curve. RESULTS: Four teams processed 1177 studies. The median age of patients was 62 years, with an interquartile range of 33 years. Nineteen teams from various academic institutions registered for the competition. Of these, 4 teams submitted their final results. No commercial entities participated in the competition. For task 1, areas under the ROC curve ranged from 0.49 to 0.59. For task 2, two teams completed the task with area under the ROC curve values of 0.57 and 0.52. For task 3, teams had little-to-no agreement with the ground truth. CONCLUSIONS: To assess the performance of artificial intelligence models in real-world clinical scenarios, we analyzed their performance in the ASFNR Artificial Intelligence Competition. The first ASFNR Competition underscored the gap between expectation and reality; and the models largely fell short in their assessments. As the integration of artificial intelligence tools into clinical workflows increases, neuroradiologists must carefully recognize the capabilities, constraints, and consistency of these technologies. Before institutions adopt these algorithms, thorough validation is essential to ensure acceptable levels of performance in clinical settings.

A Guideline for Open-Source Tools to Make Medical Imaging Data Ready for Artificial Intelligence Applications: A Society of Imaging Informatics in Medicine (SIIM) Survey.

In recent years, the role of Artificial Intelligence (AI) in medical imaging has become increasingly prominent, with the majority of AI applications approved by the FDA being in imaging and radiology in 2023. The surge in AI model development to tackle clinical challenges underscores the necessity for preparing high-quality medical imaging data. Proper data preparation is crucial as it fosters the creation of standardized and reproducible AI models while minimizing biases. Data curation transforms raw data into a valuable, organized, and dependable resource and is a fundamental process to the success of machine learning and analytical projects. Considering the plethora of available tools for data curation in different stages, it is crucial to stay informed about the most relevant tools within specific research areas. In the current work, we propose a descriptive outline for different steps of data curation while we furnish compilations of tools collected from a survey applied among members of the Society of Imaging Informatics (SIIM) for each of these stages. This collection has the potential to enhance the decision-making process for researchers as they select the most appropriate tool for their specific tasks.

Multi-harmonic near-infrared-ultraviolet dual-comb spectrometer.

Dual-comb spectroscopy in the ultraviolet (UV) and visible would enable broad bandwidth electronic spectroscopy with unprecedented frequency resolution. However, there are significant challenges in generation, detection, and processing of dual-comb data that have restricted its progress in this spectral region. In this work, we leverage robust 1550 nm few-cycle pulses to generate frequency combs in the UV-visible. We combine these combs with a wavelength multiplexed dual-comb spectrometer and simultaneously retrieve 100 MHz comb-mode-resolved spectra over three distinct harmonics at 386, 500, and 760 nm. The experiments highlight the path to continuous dual-comb coverage spanning 200-750 nm, offering extensive access to electronic transitions in atoms, molecules, and solids.

Targeted phasing of 2-200 kilobase DNA fragments with a short-read sequencer and a single-tube linked-read library method.

In the human genome, heterozygous sites refer to genomic positions with a different allele or nucleotide variant on the maternal and paternal chromosomes. Resolving these allelic differences by chromosomal copy, also known as phasing, is achievable on a short-read sequencer when using a library preparation method that captures long-range genomic information. TELL-Seq is a library preparation that captures long-range genomic information with the aid of molecular identifiers (barcodes). The same barcode is used to tag the reads derived from the same long DNA fragment within a range of up to 200 kilobases (kb), generating linked-reads. This strategy can be used to phase an entire genome. Here, we introduce a TELL-Seq protocol developed for targeted applications, enabling the phasing of enriched loci of varying sizes, purity levels, and heterozygosity. To validate this protocol, we phased 2-200 kb loci enriched with different methods: CRISPR/Cas9-mediated excision coupled with pulse-field electrophoresis for the longest fragments, CRISPR/Cas9-mediated protection from exonuclease digestion for mid-size fragments, and long PCR for the shortest fragments. All selected loci have known clinical relevance: BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, PMS2, SCN5A-SCN10A, and PKI3CA. Collectively, the analyses show that TELL-Seq can accurately phase 2-200 kb targets using a short-read sequencer.

Enhancing regional control in p16-negative oropharyngeal cancer: A propensity score-matched analysis of upfront neck dissection and definitive chemoradiotherapy.

BACKGROUND: The presence of p16 and neck disease is important predictors of prognosis for oropharyngeal squamous cell carcinoma (OPSCC). Patients who are p16-negative and have clinically node-positive (cN+) disease generally have worse oncologic outcomes. This study aimed to investigate whether upfront neck dissection (UFND) could provide potential benefits for patients with cN+ p16-negative OPSCC. METHODS: Through this retrospective study, 76 patients with cN+ p16-negative OPSCC were analyzed, those who received either definite concurrent chemoradiotherapy (CCRT group) or UFND followed by chemoradiotherapy (UFND group). The primary endpoints were regional recurrence-free survival (RRFS), disease-specific survival (DSS), and overall survival (OS). Factors associated with survival were evaluated by univariate and multivariate analysis. Survival between the two groups was compared by propensity score-matched analysis. RESULTS: Matched 23 patients in each group through propensity analysis, the UFND group showed a significantly better 5-year RRFS (94.1% vs 61.0%, p = 0.011) compared to the CCRT group. Univariate analysis revealed that UFND was the sole factor associated with regional control (hazard ratio [HR] = 0.110; 95% CI, 0.014-0.879; p = 0.037). Furthermore, the study found that the CCRT group was associated with a higher dose of radiotherapy and exhibited a significantly higher risk of mortality due to pneumonia. CONCLUSION: The study indicated that UFND followed by CCRT may be a potential treatment option for patients with cN+ p16-negative OPSCC, as it can reduce the risk of regional recurrence. Additionally, the study highlights that definite CCRT is connected to a larger dose of radiotherapy and a higher risk of fatal pneumonia. These findings could be beneficial in informing clinical decision-making and improving treatment outcomes for patients with OPSCC.

The association of patient and disease characteristics with the overtreatment of low-risk prostate cancer from 2010 to 2016.

BACKGROUND: Although active surveillance is the preferred management for low-risk prostate cancer (PCa), some men remain at risk of overtreatment with definitive local therapy. We hypothesized that baseline characteristics may be associated with overtreatment and represent a potential source of health disparities. We therefore examined the associations of patient and disease characteristics with the surgical overtreatment of low-risk PCa. METHODS: We identified men aged 45-75 years with cT1 cN0 cM0 prostate adenocarcinoma with biopsy Gleason score 6 and PSA < 10 ng/ml from 2010-2016 in the National Cancer Database (NCDB) and who underwent radical prostatectomy (RP). We evaluated the associations of baseline characteristics with clinically insignificant PCa (iPCa) at RP (i.e., "overtreatment"), defined as organ-confined (i.e., pT2) Gleason 3 + 3 disease, using multivariable logistic regression. RESULTS: We identified 36,088 men with low-risk PCa who underwent RP. The unadjusted rate of iPCa decreased during the study period, from 54.7% in 2010 to 40.0% in 2016. In multivariable analyses adjusting for baseline characteristics, older age (OR 0.98, 95% CI 0.97-0.98), later year of diagnosis (OR 0.62, 95% CI 0.57-0.67 for 2016 vs. 2010), Black race (OR 0.85, 95% CI 0.79-0.91), treatment at an academic/research program (OR 0.82, 95% CI 0.73-0.91), higher PSA (OR 0.91, 95% CI 0.90-0.92), and higher number of positive biopsy cores (OR 0.87, 95% CI 0.86-0.88) were independently associated with a lower risk of overtreatment (iPCa) at RP. Conversely, a greater number of biopsy cores sampled (OR 1.01, 95% CI 1.01-1.02) was independently associated with an increased risk of overtreatment (iPCa) at RP. CONCLUSIONS: We observed an ~27% reduction in rates of overtreatment of men with low-risk PCa over the study period. Several patient, disease, and structural characteristics are associated with detection of iPCa at RP and can inform the management of men with low-risk PCa to reduce potential overtreatment.