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Follicular lymphomas (FL) are characterized by BCL2 translocations, often detectable in blood years before FL diagnosis, but also observed in aging healthy individuals, suggesting additional lesions are required for lymphomagenesis. We directly characterized early cooperating mutations by ultradeep sequencing of prediagnostic blood and tissue specimens from 48 subjects who ultimately developed FL. Strikingly, CREBBP lysine acetyltransferase (KAT) domain mutations were the most commonly observed precursor lesions, and largely distinguished patients developing FL (14/48, 29%) from healthy adults with or without detected BCL2 rearrangements (0/13, P = 0.03 and 0/20, P = 0.007, respectively). CREBBP variants were detectable a median of 5.8 years before FL diagnosis, were clonally selected in FL tumors, and appeared restricted to the committed B-cell lineage. These results suggest that mutations affecting the CREBBP KAT domain are common lesions in FL cancer precursor cells (CPC), with the potential for discriminating subjects at risk of developing FL or monitoring residual disease.Significance:Our study provides direct evidence for recurrent genetic aberrations preceding FL diagnosis, revealing the combination of BCL2 translocation with CREBBP KAT domain mutations as characteristic committed lesions of FL CPCs. Such prediagnostic mutations are detectable years before clinical diagnosis and may help discriminate individuals at risk for lymphoma development.

Supplementary Methods and Figures S1-S5

To investigate the association between external beam radiotherapy (EBRT) and the incidence of second primary tumors in patients with thyroid cancer.Data were extracted from the Surveillance, Epidemiology, and End Results 9 database. The study cohort included patients diagnosed with thyroid cancer between 1973 and 2017. Risk factors for second primary malignancies were identified with Cox proportional hazards models. Propensity score-matched analyses were used to assess the association between EBRT and second primary malignancies.Out of 72,392 patients with thyroid cancer, 7,684 (10.6%) developed a subsequent primary malignancy. Propensity score-matched analysis demonstrated patients receiving EBRT were more likely to develop second primary malignancies [30-year cumulative incidence=35.3% (95% confidence interval (CI)=30.4-39.8% vs. 28.1% (95% CI=27.0-29.2%); hazard ratio=1.17 (95% CI=1.03-1.33)].In patients with thyroid cancer, EBRT is associated with an increased incidence of second primary malignancies.

OBJECTIVE Status epilepticus (SE) is associated with significant mortality, cost, and risk of future seizures. In one of the first studies of SE after neurosurgery, the authors assess the incidence, risk factors, and outcome of postneurosurgical SE (PNSE). METHODS Neurosurgical admissions from the MarketScan Claims and Encounters database (2007 through 2015) were assessed in a longitudinal cross-sectional sample of privately insured patients who underwent qualifying cranial procedures in the US and were older than 18 years of age. The incidence of early (in-hospital) and late (postdischarge readmission) SE and associated mortality was assessed. Procedural, pathological, demographic, and anatomical covariates parameterized multivariable logistic regression and Cox models. Multivariable logistic regression and Cox proportional hazards models were used to study the incidence of early and late PNSE. A risk-stratification simulation was performed, combining individual predictors into singular risk estimates. RESULTS A total of 197,218 admissions (218,217 procedures) were identified. Early PNSE occurred during 637 (0.32%) of 197,218 admissions for cranial neurosurgical procedures. A total of 1045 (0.56%) cases of late PNSE were identified after 187,771 procedure admissions with nonhospice postdischarge follow-up. After correction for comorbidities, craniotomy for trauma, hematoma, or elevated intracranial pressure was associated with increased risk of early PNSE (adjusted OR [aOR] 1.538, 95% CI 1.183–1.999). Craniotomy for meningioma resection was associated with an increased risk of early PNSE compared with resection of metastases and parenchymal primary brain tumors (aOR 2.701, 95% CI 1.388–5.255). Craniotomies for infection or abscess (aHR 1.447, 95% CI 1.016–2.061) and CSF diversion (aHR 1.307, 95% CI 1.076–1.587) were associated with highest risk of late PNSE. Use of continuous electroencephalography in patients with early (p < 0.005) and late (p < 0.001) PNSE rose significantly over the study time period. The simulation regression model predicted that patients at high risk for early PNSE experienced a 1.10% event rate compared with those at low risk (0.07%). Similarly, patients predicted to be at highest risk for late PNSE were significantly more likely to eventually develop late PNSE than those at lowest risk (HR 54.16, 95% CI 24.99–104.80). CONCLUSIONS Occurrence of early and late PNSE was associated with discrete neurosurgical pathologies and increased mortality. These data provide a framework for prospective validation of clinical and perioperative risk factors and indicate patients for heightened diagnostic suspicion of PNSE.

Introduction While recent studies have focused on confirming satisfaction with telemedicine during the coronavirus disease 2019 (COVID-19) era, we leveraged a novel survey instrument to identify associations between patient experience and telemedicine-specific factors such as device selection, audio/visual resolution, and connection stability. Methods Telemedicine visit data were gathered from our institution between June 22, 2020 and February 14, 2021. Each patient indicated their overall visit score, likelihood-to-recommend (LTR) score, and device used for the encounter. Remaining questions were randomly distributed to patients to ensure equal distribution across respondents. Results Over 34 weeks, there were 901 unique neurosurgical telemedicine visits linked to a post-visit survey at our institution. The LTR top box score percentage showed no significant change across 34 weeks (p = 0.218). After adjusting across available covariates, patients who experienced wait times exceeding 20 min were significantly less likely to report high overall scores (aOR: 0.12; 95% CI: 0.03–0.41; p = 0.001). Patients who indicated they were less able to understand the provider (aOR: 0.22; 95% CI: 0.07–0.66; p = 0.007), or who indicated the provider was not able to properly see them (aOR: 0.11; 95% CI: 0.03–0.43; p = 0.002) were associated with substantially lower overall scores. Visits with interrupted connectivity or those forced to move to a regular phone call were not important predictors of overall score. Conclusions In the largest description of patient satisfaction with telemedicine in the neurosurgical setting during the COVID-19 era, we identified timely and high-quality physician-patient visualization and communication as among the most important predictors of patient satisfaction in virtual settings.

BACKGROUND CONTEXT Despite increased awareness of the ongoing opioid epidemic, opioid and benzodiazepine use remain high after spine surgery. In particular, long-term co-prescription of opioids and benzodiazepines have been linked to high risk of overdose-associated death. Tumor patients represent a unique subset of spine surgery patients and few studies have attempted to develop predictive models to anticipate long-term opioid and benzodiazepine use after spinal tumor resection. METHODS The IBM Watson Health MarketScan Database and Medicare Supplement were assessed to identify admissions for intradural tumor resection between 2007 and 2015. Adult patients were required to have at least 6 months of continuous preadmission baseline data and 12 months of continuous postdischarge follow-up. Primary outcomes were long-term opioid and benzodiazepine use, defined as at least 6 prescriptions within 12 months. Secondary outcomes were durations of opioid and benzodiazepine prescribing. Logistic regression models, with and without regularization, were trained on an 80% training sample and validated on the withheld 20%. RESULTS A total of 1,942 patients were identified. The majority of tumors were extramedullary (74.8%) and benign (62.5%). A minority of patients received arthrodesis (9.2%) and most patients were discharged to home (79.1%). Factors associated with postdischarge opioid use duration include tumor malignancy (vs benign, B=19.8 prescribed-days/year, 95% confidence interval [CI] 1.1–38.5) and intramedullary compartment (vs extramedullary, B=18.1 prescribed-days/year, 95% CI 3.3–32.9). Pre- and perioperative use of prescribed nonsteroidal anti-inflammatory drugs and gabapentin/pregabalin were associated with shorter and longer duration opioid use, respectively. History of opioid and history of benzodiazepine use were both associated with increased postdischarge opioid and benzodiazepine use. Intramedullary location was associated with longer duration postdischarge benzodiazepine use (B=10.3 prescribed-days/year, 95% CI 1.5–19.1). Among assessed models, elastic net regularization demonstrated best predictive performance in the withheld validation cohort when assessing both long-term opioid use (area under curve [AUC]=0.748) and long-term benzodiazepine use (AUC=0.704). Applying our model to the validation set, patients scored as low-risk demonstrated a 4.8% and 2.4% risk of long-term opioid and benzodiazepine use, respectively, compared to 35.2% and 11.1% of high-risk patients. CONCLUSIONS We developed and validated a parsimonious, predictive model to anticipate long-term opioid and benzodiazepine use early after intradural tumor resection, providing physicians opportunities to consider alternative pain management strategies.

PURPOSE Clinical outcomes of patients with CNS lymphomas (CNSLs) are remarkably heterogeneous, yet identification of patients at high risk for treatment failure is challenging. Furthermore, CNSL diagnosis often remains unconfirmed because of contraindications for invasive stereotactic biopsies. Therefore, improved biomarkers are needed to better stratify patients into risk groups, predict treatment response, and noninvasively identify CNSL. PATIENTS AND METHODS We explored the value of circulating tumor DNA (ctDNA) for early outcome prediction, measurable residual disease monitoring, and surgery-free CNSL identification by applying ultrasensitive targeted next-generation sequencing to a total of 306 tumor, plasma, and CSF specimens from 136 patients with brain cancers, including 92 patients with CNSL. RESULTS Before therapy, ctDNA was detectable in 78% of plasma and 100% of CSF samples. Patients with positive ctDNA in pretreatment plasma had significantly shorter progression-free survival (PFS, P < .0001, log-rank test) and overall survival (OS, P = .0001, log-rank test). In multivariate analyses including established clinical and radiographic risk factors, pretreatment plasma ctDNA concentrations were independently prognostic of clinical outcomes (PFS HR, 1.4; 95% CI, 1.0 to 1.9; P = .03; OS HR, 1.6; 95% CI, 1.1 to 2.2; P = .006). Moreover, measurable residual disease detection by plasma ctDNA monitoring during treatment identified patients with particularly poor prognosis following curative-intent immunochemotherapy (PFS, P = .0002; OS, P = .004, log-rank test). Finally, we developed a proof-of-principle machine learning approach for biopsy-free CNSL identification from ctDNA, showing sensitivities of 59% (CSF) and 25% (plasma) with high positive predictive value. CONCLUSION We demonstrate robust and ultrasensitive detection of ctDNA at various disease milestones in CNSL. Our findings highlight the role of ctDNA as a noninvasive biomarker and its potential value for personalized risk stratification and treatment guidance in patients with CNSL. [Media: see text]

Retrospective cohort.Due to anterior cervical discectomy and fusion (ACDF) popularity, it is important to predict postoperative complications, unfavorable 90-day readmissions, and two-year reoperations to improve surgical decision-making, prognostication, and planning.Machine learning has been applied to predict postoperative complications for ACDF; however, studies were limited by sample size and model type. These studies achieved ≤0.70 area under the curve (AUC). Further approaches, not limited to ACDF, focused on specific complication types and resulted in AUC between 0.70 and 0.76.The IBM MarketScan Commercial Claims and Encounters Database and Medicare Supplement were queried from 2007 to 2016 to identify adult patients who underwent an ACDF procedure (N=176,816). Traditional machine learning algorithms, logistic regression, and support vector machines, were compared with deep neural networks to predict: 90-day postoperative complications, 90-day readmission, and two-year reoperation. We further generated random deep learning model architectures and trained them on the 90-day complication task to approximate an upper bound. Last, using deep learning, we investigated the importance of each input variable for the prediction of 90-day postoperative complications in ACDF.For the prediction of 90-day complication, 90-day readmission, and two-year reoperation, the deep neural network-based models achieved AUC of 0.832, 0.713, and 0.671. Logistic regression achieved AUCs of 0.820, 0.712, and 0.671. Support vector machine approaches were significantly lower. The upper bound of deep learning performance was approximated as 0.832. Myelopathy, age, human immunodeficiency virus, previous myocardial infarctions, obesity, and documentary weakness were found to be the strongest variable to predict 90-day postoperative complications.The deep neural network may be used to predict complications for clinical applications after multicenter validation. The results suggest limited added knowledge exists in interactions between the input variables used for this task. Future work should identify novel variables to increase predictive power.

Background: The coronavirus disease 2019 (COVID-19) pandemic heralded a number of indirect perturbations to patient behavior and disease epidemiology, and mounting evidence suggests that the COVID-19 pandemic may have exacerbated underlying health disparities along racial and socioeconomic (SES) groups for acute ischemic stroke (AIS). We used 1 large national insurance database to identify whether patient demographics, disease severity, or mechanical thrombectomy (MT) rates changed for the treatment and management of AIS during COVID-19. Methods: AIS patient records were queried from the Clinformatics® Data Mart Optum SES Database from the following 2 time periods: March 1, 2019-June 30, 2019 (pre-COVID-19), and March 1, 2020–June 30, 2020 (COVID-19). The database contains the longitudinal healthcare claims of approximately 77 million patients covered by a major insurance provider between 2003 and June 30, 2020 across all 50 states. Interrupted time-series analyses were used to assess trend differences before and after the COVID-19 pandemic. Results: During the pre-COVID-19 period (March 1, 2019-June 30, 2019), there were 9,072 patients who presented for AIS, compared to 7,366 during COVID-19 (March 1, 2020-June 30, 2020). In both periods, the majority of patients were white (66.83% pre-COVID-19 and 67.91% during COVID-19). The average hospitalization duration was not different during the 2 time periods (p = 0.632), nor were rates of MT (p = 0.260). Total inpatient costs rose slightly for the COVID-19 period (USD 30,739 vs. USD 29,406; p = 0.015), and the median National Institutes of Health Stroke Scale (NIHSS) score was higher during CO­VID-19 (5 vs. 4; p = 0.023). When longitudinal trends were assessed for rates of MT and average NIHSS score for black and white patients, no differences were noted during the CO­VID-19 pandemic. Patients without any undergraduate experience did not present with AIS in increasing or decreasing incidence during COVID-19 (p = 0.268), but they did undergo declining rates of MT (p = 0.013). Conclusions: In the largest SES analysis of AIS patients during the COVID-19 era, we found that several SES factors, including race and income, did not seem to significantly impact utilization of MT for the treatment of AIS or the severity of the stroke at presentation.

OBJECTIVE Although past studies have associated external-beam radiation therapy (EBRT) with higher incidences of secondary neoplasms (SNs), its effect on SN development from pediatric low-grade gliomas (LGGs), defined as WHO grade I and II gliomas of astrocytic or oligodendrocytic origin, is not well understood. Utilizing a national cancer registry, the authors sought to characterize the risk of SN development after EBRT treatment of pediatric LGG. METHODS A total of 1245 pediatric patient (aged 0–17 years) records from 1973 to 2015 were assembled from the Surveillance, Epidemiology, and End Results (SEER) database. Univariable and multivariable subdistribution hazard regression models were used to evaluate the prognostic impact of demographic, tumor, and treatment-related covariates. Propensity score matching was used to balance baseline characteristics. Cumulative incidence analyses measured the time to, and rate of, SN development, stratified by receipt of EBRT and controlled for competing mortality risk. The Fine and Gray semiparametric model was used to estimate future SN risk in EBRT- and non–EBRT-treated pediatric patients. RESULTS In this study, 366 patients received EBRT and 879 did not. Forty-six patients developed SNs after an LGG diagnosis, and 27 of these patients received EBRT (OR 3.61, 95% CI 1.90–6.95; p < 0.001). For patients alive 30 years from the initial LGG diagnosis, the absolute risk of SN development in the EBRT-treated cohort was 12.61% (95% CI 8.31–13.00) compared with 4.99% (95% CI 4.38–12.23) in the non–EBRT-treated cohort (p = 0.013). Cumulative incidence curves that were adjusted for competing events still demonstrated higher rates of SN development in the EBRT-treated patients with LGGs. After matching across available covariates and again adjusting for the competing risk of mortality, a clear association between EBRT and SN development remained (subhazard ratio 2.26, 95% CI 1.21–4.20; p = 0.010). CONCLUSIONS Radiation therapy was associated with an increased risk of future SNs for pediatric patients surviving LGGs. These data suggest that the long-term implications of EBRT should be considered when making treatment decisions for this patient population

Introduction Venous thromboembolism (VTE) management increasingly involves anticoagulation with direct oral anticoagulants (DOACs). Few studies have used competing-risks analyses to ascertain the mortality-adjusted hemorrhage and recurrent VTE (rVTE) risk of individual DOACs. Furthermore, hemorrhage risk factors in patients treated with apixaban remain underexplored. Materials and methods Patients diagnosed with VTE receiving anticoagulation were identified from the Optum Clinformatics Data Mart (2003–2019). Study endpoints included readmissions for intracranial hemorrhage (ICH), non-intracranial hemorrhage (non-ICH hemorrhage), and rVTE. Coarsened exact matching was used to balance baseline clinical characteristics. Complication incidence was evaluated using a competing-risks framework. We additionally modeled hemorrhage risk in apixaban-treated patients. Results Overall, 225,559 patients were included, of whom 34,201 received apixaban and 46,007 received rivaroxaban. Compared to rivaroxaban, apixaban was associated with decreased non-ICH hemorrhage (sHR = 0.560, 95%CI = 0.423–0.741), but not ICH, and rVTE (sHR = 0.802, 95%CI = 0.651–0.988) risk. This was primarily in emergent readmissions (sHR[emergent hemorrhage] = 0.515, 95%CI = 0.372–0.711; sHR[emergent rVTE] = 0.636, 95%CI = 0.488–0.830). Contributors to emergent hemorrhage in apixaban-treated patients include older age (sHR = 1.025, 95%CI = 1.011–1.039), female sex (sHR = 1.662, 95%CI = 1.252–2.207), prior prescription antiplatelet therapy (sHR = 1.591, 95%CI = 1.130–2.241), and complicated hypertension (sHR = 1.936, 95%CI = 1.134–3.307). Patients anticipated to be “high-risk” experienced elevated ICH (sHR = 3.396, 95%CI = 1.375–8.388) and non-ICH hemorrhage (sHR = 3.683, 95%CI = 2.957–4.588) incidence. Conclusions In patients with VTE receiving anticoagulation, apixaban was associated with reduced non-ICH hemorrhage and rVTE risk, compared to rivaroxaban. Risk reduction was restricted to emergent readmissions. We present a risk-stratification approach to predict hemorrhage in patients receiving apixaban, potentially guiding future clinical decision-making.

Circulating tumor DNA (ctDNA) is an emerging biomarker for many cancers, but the limited sensitivity of current detection methods reduces its utility for diagnosing minimal residual disease. Here we describe phased variant enrichment and detection sequencing (PhasED-Seq), a method that uses multiple somatic mutations in individual DNA fragments to improve the sensitivity of ctDNA detection. Leveraging whole-genome sequences from 2,538 tumors, we identify phased variants and their associations with mutational signatures. We show that even without molecular barcodes, the limits of detection of PhasED-Seq outperform prior methods, including duplex barcoding, allowing ctDNA detection in the parts-per-million range in patient samples. We profiled 678 specimens from 213 patients with B-cell lymphomas, including serial cell-free DNA samples before and during therapy for diffuse large B-cell lymphoma. In patients with undetectable ctDNA by CAPP-Seq after two cycles of therapy, an additional 25% have ctDNA detectable by PhasED-Seq and have worse outcomes. Finally, we demonstrate the application of PhasED-Seq to solid tumors., Editorial summary The sensitivity of circulating tumor DNA detection is improved by identifying sequences with two or more mutations.

Research has uncovered heterogeneity and inefficiencies in the management of idiopathic low back pain, but few studies have examined longitudinal care patterns following newly diagnosed neck pain.To understand health care utilization in patients with new-onset idiopathic neck pain.This cross-sectional study used nationally sourced longitudinal data from the IBM Watson Health MarketScan claims database (2007-2016). Participants included adult patients with newly diagnosed neck pain, no recent opioid use, and at least 1 year of continuous postdiagnosis follow-up. Exclusion criteria included prior or concomitant diagnosis of traumatic cervical disc dislocation, vertebral fractures, myelopathy, and/or cancer. Only patients with at least 1 year of prediagnosis lookback were included. Data analysis was performed from January 2021 to January 2022.The primary outcome of interest was 1-year postdiagnosis health care expenditures, including costs, opioid use, and health care service utilization. Early services were those received within 30 days of diagnosis. Multivariable regression models and regression-adjusted statistics were used.In total, 679 030 patients (310 665 men [45.6%]) met the inclusion criteria, of whom 7858 (1.2%) underwent surgery within 1 year of diagnosis. The mean (SD) age was 44.62 (14.87) years among nonsurgical patients and 49.69 (9.53) years among surgical patients. Adjusting for demographics and comorbidities, 1-year regression-adjusted health care costs were $24 267.55 per surgical patient and $515.69 per nonsurgical patient. Across all health care services, $95 379 949 was accounted for by nonsurgical patients undergoing early imaging who did not receive any additional conservative therapy or epidural steroid injections, for a mean (SD) of $477.53 ($1375.60) per patient and median (IQR) of $120.60 ($20.70-$452.37) per patient. On average, patients not undergoing surgery, physical therapy, chiropractic manipulative therapy, or epidural steroid injection, who underwent either early advanced imaging (magnetic resonance imaging or computed tomography) or both early advanced and radiographic imaging, accumulated significantly elevated health care costs ($850.69 and $1181.67, respectively). Early conservative therapy was independently associated with 24.8% (95% CI, 23.5%-26.2%) lower health care costs.In this cross-sectional study, early imaging without subsequent intervention was associated with significantly increased health care spending among patients with newly diagnosed idiopathic neck pain. Early conservative therapy was associated with lower costs, even with increased frequency of therapeutic services, and may have reduced long-term care inefficiency.

OBJECTIVE Traumatic brain injury (TBI) is a major cause of mortality and morbidity in Uganda and other low- and middle-income countries (LMICs). Due to the difficulty of long-term in-person follow-up, there is a paucity of literature on longitudinal outcomes of TBI in LMICs. Using a scalable phone-centered survey, this study attempted to investigate factors associated with both mortality and quality of life in Ugandan patients with TBI. METHODS A prospective registry of adult patients with TBI admitted to the neurosurgical ward at Mulago National Referral Hospital was assembled. Long-term follow-up was conducted between 10.4 and 30.5 months after discharge (median 18.6 months). Statistical analyses included univariable and multivariable logistic regression and Cox proportional hazards regression to elucidate factors associated with mortality and long-term recovery. RESULTS A total of 1274 adult patients with TBI were included, of whom 302 (23.7%) died as inpatients. Patients who died as inpatients received surgery less frequently (p < 0.001), had more severe TBI at presentation (p < 0.001), were older (p < 0.001), and were more likely to be female (p < 0.0001). Patients presenting with TBI resulting from assault were at reduced risk of inpatient death compared with those presenting with TBI caused by road traffic accidents (OR 0.362, 95% CI 0.128–0.933). Inpatient mortality and postdischarge mortality prior to follow-up were 23.7% and 9%, respectively. Of those discharged, 60.8% were reached through phone interviews. Higher Glasgow Coma Scale score at discharge (continuous HR 0.71, 95% CI 0.53–0.94) was associated with improved long-term survival. Tracheostomy (HR 4.38, 95% CI 1.05–16.7) and older age (continuous HR 1.03, 95% CI 1.009–1.05) were associated with poor long-term outcomes. More than 15% of patients continued to suffer from TBI sequelae years after the initial injury, including seizures (6.1%) and depression (10.0%). Despite more than 60% of patients seeking follow-up healthcare visits, mortality was still 9% among discharged patients, suggesting a need for improved longitudinal care to monitor recovery progress. CONCLUSIONS Inpatient and postdischarge mortality remain high following admission to Uganda’s main tertiary hospital with the diagnosis of TBI. Furthermore, posttraumatic sequelae, including seizures and depression, continue to burden patients years after discharge. Effective scalable solutions, including phone interviews, are needed to elucidate and address factors limiting in-hospital capacity and access to follow-up healthcare.

Purpose Although consensus guidelines for postresection stereotactic radiosurgery (SRS) for brain metastases recommend the surgical corridor leading to the resection cavity be included in the SRS plan, no study has reported patterns of tumor recurrence based on inclusion or exclusion of the corridor as a target. We reviewed tumor control and toxicity outcomes of postresection SRS for deep brain metastases based on whether or not the surgical corridor was targeted. Materials and Methods We retrospectively reviewed patients who had resected brain metastases treated with SRS between 2007 and 2018 and included only “deep” tumors (defined as located ≥1.0 cm from the pial surface before resection). Results In 66 deep brain metastases in 64 patients, the surgical corridor was targeted in 43 (65%). There were no statistical differences in the cumulative incidences of progression at 12 months for targeting versus not targeting the corridor, respectively, for overall local failure 2% (95% confidence interval [CI], 0%-11%) versus 9% (95% CI, 1%-25%; P = .25), corridor failure 0% (95% CI, 0%-0%) versus 9% (95% CI, 1%-25%; P = .06), cavity failure 2% (95% CI, 0%-11%) versus 0% (95% CI, 0%-0%; P = .91), and adverse radiation effect 5% (95% CI, 1%-15%) versus 13% (95% CI, 3%-30%; P = .22). Leptomeningeal disease (7%; 95% CI, 2%-18%) versus 26% (95% CI, 10%-45%; P = .03) was higher in those without the corridor targeted. Conclusions Omitting the surgical corridor in postoperative SRS for resected brain metastases was not associated with statistically significant differences in corridor or cavity recurrence or adverse radiation effect. As seen in recent prospective trials of postresection SRS, the dominant pattern of progression is within the resection cavity; omission of the corridor would yield a smaller SRS volume that could allow for dose escalation to potentially improve local cavity control.

Medullary thyroid carcinoma (MTC) often presents with advanced disease and takes an aggressive course as compared with more well-differentiated thyroid cancers. The role of adjuvant therapy, specifically external beam radiotherapy (EBRT), remains disputed. This study investigated the impact of EBRT on survival in MTC.Cross-sectional analysis of a national database.Patients with MTC were identified from the SEER program (Surveillance, Epidemiology, and End Results).Collected variables included age, sex, race, T and N stages, lymph node yield, and use of EBRT. Propensity score matching was performed to determine the association of EBRT with overall and disease-specific survival.A total of 2046 patients with locoregional MTC were identified. Of these, 152 received EBRT. Patients receiving EBRT were older and had more advanced disease. EBRT was not associated with differences in overall survival (hazard ratio, 1.12; 95% CI, 0.76-1.65) or disease-specific survival (1.66; 0.93-2.95), as well as in subset analysis of age and disease extent. Long-term overall survival was similar, with 77.3% (95% CI, 70.1%-85.3%) and 58.3% (48.2%-70.5%) of patients without EBRT alive at 5 and 10 years, respectively (vs 70.7% [63.2%-79.1%] and 52.3% [43.3%-63.2%] of patients with EBRT). There were no differences in 5- and 10-year disease-specific survival.EBRT was not associated with improved overall or disease-specific survival in patients with MTC. Decisions regarding EBRT must be made with consideration of morbidity relative to benefit for individual patients.

OBJECTIVECavernous malformations (CMs) are commonly treated cerebrovascular anomalies in the pediatric population; however, the data on radiographic recurrence of pediatric CMs after surgery are limited. The authors aimed to study the clinical presentation, outcomes, and recurrence rate following surgery for a large cohort of CMs in children.METHODSPediatric patients (≤ 18 years old) who had a CM resected at a single institution were identified and retrospectively reviewed. Fisher’s exact test of independence was used to assess differences in categorical variables. Survival curves were evaluated using the Mantel-Cox method.RESULTSFifty-three patients aged 3 months to 18 years underwent resection of 74 symptomatic CMs between 1996 and 2018 at a single institution. The median length of follow-up was 5.65 years. Patients most commonly presented with seizures (45.3%, n = 24) and the majority of CMs were cortical (58.0%, n = 43). Acute radiographic hemorrhage was common at presentation (64.2%, n = 34). Forty-two percent (n = 22) of patients presented with multiple CMs, and they were more likely to develop de novo lesions (71%) compared to patients presenting with a single CM (3.4%). Both radiographic hemorrhage and multiple CMs were independently prognostic for a higher risk of the patient requiring subsequent surgery. Fifty percent (n = 6) of the 12 patients with both risk factors required additional surgery within 2.5 years of initial surgery compared to none of the patients with neither risk factor (n = 9).CONCLUSIONSPatients with either acute radiographic hemorrhage or multiple CMs are at higher risk for subsequent surgery and require long-term MRI surveillance. In contrast, patients with a single CM are unlikely to require additional surgery and may require less frequent routine imaging.

BackgroundWhile dual antiplatelet therapy (dAPT) is standard of care following carotid artery stenting (CAS), the optimal dAPT regimen and duration has not been established.MethodsWe canvassed a large national database (IBM MarketScan) to identify patients receiving carotid endarterectomy (CEA) or CAS for treatment of ischemic stroke or carotid artery stenosis from 2007 to 2016. We performed univariable and multivariable regression methods to evaluate the impact of covariates on post-CAS stroke-free survival, including post-discharge antiplatelet therapy.ResultsA total of 79 084 patients diagnosed with ischemic stroke or carotid stenosis received CEA (71 178; 90.0%) or CAS (7906; 10.0%). After adjusting for covariates, ConclusionsIncreased duration of post-CAS dAPT is associated with lower rates of readmissions for stroke, and with increased risk of hemorrhagic complications, particularly extracranial hemorrhage. The potential benefit of prolonging dAPT with regard to ischemic complications must be balanced with the corresponding increased risk of predominantly extracranial hemorrhagic complications.

Radiologic screening of high-risk adults reduces lung-cancer-related mortality1,2; however, a small minority of eligible individuals undergo such screening in the United States3,4. The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq)5, a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent. Compared with tumour-derived mutations, clonal haematopoiesis mutations occur on longer cfDNA fragments and lack mutational signatures that are associated with tobacco smoking. Integrating these findings with other molecular features, we develop and prospectively validate a machine-learning method termed 'lung cancer likelihood in plasma' (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls. This approach achieves performance similar to that of tumour-informed ctDNA detection and enables tuning of assay specificity in order to facilitate distinct clinical applications. Our findings establish the potential of cfDNA for lung cancer screening and highlight the importance of risk-matching cases and controls in cfDNA-based screening studies.

OBJECTIVE Craniosynostosis is characterized by the premature fusion of at least one cranial suture. Although evidence suggests that patients with both syndromic and nonsyndromic craniosynostosis may benefit from developmental, behavioral, and mental health support, data on utilization of healthcare services are lacking. In this study the authors compared utilization of mental health care, rehabilitation therapies, and other specialty medical services among children with craniosynostosis, children with plagiocephaly, and healthy controls. METHODS The Optum Clinformatics Data Mart database was queried to identify 1340 patients with craniosynostosis, of whom 200 had syndromic craniosynostosis. Long-term utilization of mental health care, rehabilitation therapies, and other medical services up to the age of 6 years was calculated. Rates of utilization were compared to healthy controls (n = 1577) and children with plagiocephaly (n = 1249). RESULTS Patients with syndromic and nonsyndromic craniosynostosis used mental health care, occupational therapy, speech–language pathology, and other medical services at similar rates (p = 0.1198, p > 0.9999, p = 0.1097, and p = 0.8119, respectively). Mental health services were used more frequently by patients with craniosynostosis (11.0% in patients with syndromic craniosynostosis and 7.5% in those with nonsyndromic craniosynostosis) compared to patients in the plagiocephaly (5.0%, p = 0.0020) and healthy control (2.9%, p < 0.0001) cohorts. Rehabilitation therapies were more frequently used by patients with syndromic craniosynostosis and plagiocephaly (16.0% and 14.1%, respectively), which was significantly higher than use by healthy controls (p < 0.0001). Other medical subspecialty services (developmental pediatrics, ophthalmology, optometry, and audiology) were used by 37.0% of patients with craniosynostosis, compared with 20.9% (p < 0.0001) and 15.1% (p < 0.0001) of patients with plagiocephaly and healthy controls, respectively. Among patients with craniosynostosis, utilization did not differ by race or household income, but it was not uniform by age. Whereas ophthalmology utilization did not differ by age (p = 0.1003), mental health care was most commonly used among older children (p = 0.0107). CONCLUSIONS In this study, the authors demonstrate that rates of utilization of mental health care, rehabilitation therapies, and other medical subspecialty services are similar between patients with syndromic and those with nonsyndromic craniosynostosis, but higher than in healthy controls. Although surgical correction may be considered an isolated event, providers and parents need to monitor all children with craniosynostosis—syndromic and nonsyndromic—for developmental and mental health support longitudinally. Future work should explore risk factors driving utilization, including suture involvement, repair type, and comorbidities.

BACKGROUND: New ultrasensitive methods for detecting residual disease after surgery are needed in human papillomavirus–associated oropharyngeal squamous cell carcinoma (HPV+OPSCC). METHODS: To determine whether the clearance kinetics of circulating tumor human papillomavirus DNA (ctHPVDNA) is associated with postoperative disease status, a prospective observational study was conducted in 33 patients with HPV+OPSCC undergoing surgery. Blood was collected before surgery, postoperative days 1 (POD 1), 7, and 30 and with follow-up. A subcohort of 12 patients underwent frequent blood collections in the first 24 hours after surgery to define early clearance kinetics. Plasma was run on custom droplet digital polymerase chain reaction (ddPCR) assays for HPV genotypes 16, 18, 33, 35, and 45. RESULTS: In patients without pathologic risk factors for recurrence who were observed after surgery, ctHPVDNA rapidly decreased to 350 copies/mL) and remained elevated until adjuvant treatment (n = 3/3). Patients with intermediate POD 1 ctHPVDNA levels (1.2–58.4 copies/mL) all possessed pathologic risk factors for microscopic residual disease (n = 9/9). POD 1 ctHPVDNA levels were higher in patients with known adverse pathologic risk factors such as extranodal extension >1 mm (P = .0481) and with increasing lymph nodes involved (P = .0453) and were further associated with adjuvant treatment received (P = .0076). One of 33 patients had a recurrence that was detected by ctHPVDNA 2 months earlier than clinical detection. CONCLUSIONS: POD 1 ctHPVDNA levels are associated with the risk of residual disease in patients with HPV+OPSCC undergoing curative intent surgery and thus could be used as a personalized biomarker for selecting adjuvant treatment in the future.

1) To determine the prevalence polysomnogram (PSG) and continuous positive airway pressure (CPAP) therapy use in children who received adenotonsillectomy (AT) for sleep symptoms. 2) To identify health care disparities in these regards.Retrospective database analysis.This study used data from Optum (Health Services Innovation Company) to identify 92,490 children who received AT for sleep symptoms between 2004 and 2018. Prevalence of preoperative PSG and postoperative PSG and CPAP were described. Clinical and demographic characteristics were compared between children who had preoperative PSG and those who did not. Characteristics of children with trisomy 21 (T21) were compared to assess PSG and CPAP use in a high-risk cohort. Predictive modeling was used to identify patient characteristics associated with postoperative PSG and CPAP use.Preoperative PSG was obtained in 5.5% of children overall and 33.2% of children with T21. Male sex, obesity, other medical comorbidities, non-White race/ethnicity, and higher parent education were associated with preoperative PSG. Fewer than 3% of children received postoperative PSGs and approximately 3% went on to receive CPAP therapy postoperatively. Multiple logistic regression showed that age at surgery, male sex, obesity, other medical comorbidities, non-White race/ethnicity, and higher parent education were associated with postoperative PSG and CPAP use.This study described the prevalence pre-AT PSG use and post-AT PSG and CPAP use for persistent symptoms and identified sleep health care disparities in these regards. These results show that increased, equitable access to PSG is needed in children, particularly in the workup and treatment persistent symptoms after AT.4 Laryngoscope, 133:184-188, 2023.

Background Surgical resection is a mainstay in the treatment of pediatric brain tumors to achieve tissue diagnosis and tumor debulking. While maximal safe resection of tumors is desired, it can be challenging to differentiate normal brain from neoplastic tissue using only microscopic visualization, intraoperative navigation, and tactile feedback. Here, we investigate the potential for Raman spectroscopy (RS) to accurately diagnose pediatric brain tumors intraoperatively. Methods Using a rapid acquisition RS device, we intraoperatively imaged fresh ex vivo brain tissue samples from 29 pediatric patients at the Lucile Packard Children’s Hospital between October 2018 and March 2020 in a prospective fashion. Small tissue samples measuring 2-4 mm per dimension were obtained with each individual tissue sample undergoing multiple unique Raman spectra acquisitions. All tissue samples from which Raman spectra were acquired underwent individual histopathology review. A labeled dataset of 678 unique Raman spectra gathered from 160 samples was then used to develop a machine learning model capable of (1) differentiating normal brain from tumor tissue and (2) normal brain from low-grade glioma (LGG) tissue. Results Trained logistic regression model classifiers were developed using our labeled dataset. Model performance was evaluated using leave-one-patient-out cross-validation. The area under the curve (AUC) of the receiver-operating characteristic (ROC) curve for our tumor vs normal brain model was 0.94. The AUC of the ROC curve for LGG vs normal brain was 0.91. Conclusions Our work suggests that RS can be used to develop a machine learning-based classifier to differentiate tumor vs non-tumor tissue during resection of pediatric brain tumors.

Glioblastoma (GBM) is the most common primary central nervous system malignancy in adults and continues to carry a poor prognosis despite standard of care involving surgical resection and concomitant chemoradiotherapy. Recently, immunotherapy has become a rapidly evolving area of novel therapies for various cancers. For gliomas, antibodies including immune checkpoint inhibitors, such as anti-PD-1, and agents targeting tumor neovascularization were studied, but results from clinical trials show no survival benefit with immunotherapy in GBM. Combination immunotherapy and novel forms of targeted therapy are critical to ongoing and current GBM research. Because the glioma microenvironment is so immunosuppressive, therapies that address tumor-promoting cell populations and mechanisms are promising and could be synergistic with existing agents. Chemokine and chemokine receptors important to GBM development and malignancy include CXCL12 and its receptors CXCR4 and CXCR7, and targeting those axes has shown promise in improving survival rates in glioma models and deserves ongoing study in patients.

Most relapsed/refractory large B cell lymphoma (r/rLBCL) patients receiving anti-CD19 chimeric antigen receptor (CAR19) T cells relapse. To characterize determinants of resistance, we profiled over 700 longitudinal specimens from two independent cohorts (n = 65 and n = 73) of r/rLBCL patients treated with axicabtagene ciloleucel. A method for simultaneous profiling of circulating tumor DNA (ctDNA), cell-free CAR19 (cfCAR19) retroviral fragments, and cell-free T cell receptor rearrangements (cfTCR) enabled integration of tumor and both engineered and non-engineered T cell effector-mediated factors for assessing treatment failure and predicting outcomes. Alterations in multiple classes of genes are associated with resistance, including B cell identity (PAX5 and IRF8), immune checkpoints (CD274), and those affecting the microenvironment (TMEM30A). Somatic tumor alterations affect CAR19 therapy at multiple levels, including CAR19 T cell expansion, persistence, and tumor microenvironment. Further, CAR19 T cells play a reciprocal role in shaping tumor genotype and phenotype. We envision these findings will facilitate improved chimeric antigen receptor (CAR) T cells and personalized therapeutic approaches.

While machine learning has occupied a niche in clinical medicine for decades, continued method development and increased accessibility of medical data have led to broad diversification of approaches. These range from humble regression-based models to more complex artificial neural networks; yet, despite heterogeneity in foundational principles and architecture, the spectrum of machine learning approaches to clinical prediction modeling have invariably led to the development of algorithms advancing our ability to provide optimal care for our patients. In this chapter, we briefly review early machine learning approaches in medicine before delving into common approaches being applied for clinical prediction modeling today. For each, we offer a brief introduction into theory and application with accompanying examples from the medical literature. In doing so, we present a summarized image of the current state of machine learning and some of its many forms in medical predictive modeling.

While machine learning has occupied a niche in clinical medicine for decades, continued method development and increased accessibility of medical data have led to broad diversification of approaches. These range from humble regression-based models to more complex artificial neural networks; yet, despite heterogeneity in foundational principles and architecture, the spectrum of machine learning approaches to clinical prediction modeling have invariably led to the development of algorithms advancing our ability to provide optimal care for our patients. In this chapter, we briefly review early machine learning approaches in medicine before delving into common approaches being applied for clinical prediction modeling today. For each, we offer a brief introduction into theory and application with accompanying examples from the medical literature. In doing so, we present a summarized image of the current state of machine learning and some of its many forms in medical predictive modeling.

OBJECTIVE Optimal management of pediatric Chiari malformation type I (CM-I) is much debated, chiefly due to the lack of validated tools for outcome assessment, with very few tools incorporating patient-centered measures of health-related quality of life (HRQOL). Although posterior fossa decompression (PFD) benefits a subset of patients, prediction of its impact across patients is challenging. The primary aim of this study was to investigate the role of patient-centered HRQOL measures in the assessment and prediction of outcomes after PFD. METHODS The authors collected HRQOL data from a cohort of 20 pediatric CM-I patients before and after PFD. The surveys included assessments of selected Patient-Reported Outcomes Measurement Information System (PROMIS) health domains and were used to generate the PROMIS preference (PROPr) score, which is a measure of HRQOL. PROMIS is a reliable standardized measure of HRQOL domains such as pain, fatigue, depression, and physical function, which are all relevant to CM-I. The authors then compared the PROPr scores with Chicago Chiari Outcome Scale (CCOS) scores derived from time-matched clinical documentation. Finally, the authors used the PROPr scores as an outcome measure to predict postsurgical HRQOL improvement at 1 year on the basis of patient demographic characteristics, comorbidities, and radiological and physical findings. The Wilcoxon signed-rank test, Mann-Whitney U-test, and Kendall’s correlation were used for statistical analysis. RESULTS Aggregate analysis revealed improvement of pain severity after PFD (p = 0.007) in anatomical patterns characteristic of CM-I. Most PROMIS domain scores trended toward improvement after surgery, with anxiety and pain interference reaching statistical significance (p < 0.002 and p < 0.03, respectively). PROPr scores also significantly improved after PFD (p < 0.008). Of the baseline patient characteristics, preexisting scoliosis was the most accurate negative predictor of HRQOL improvement after PFD (median −0.095 vs 0.106, p < 0.001). A correlation with modest magnitude (Kendall’s tau range 0.19–0.47) was detected between the patient-centered measures and CCOS score. CONCLUSIONS The authors observed moderate improvement of HRQOL, when measured using a modified panel of PROMIS question banks, in this pilot cohort of pediatric CM-I patients after PFD. Further investigations are necessary to validate this tool for children with CM-I and to determine whether these scores correlate with clinical and radiographic findings.

OBJECTIVE Neonatal intraventricular hemorrhage (IVH) is a major cause of mortality and morbidity, particularly following premature birth. Even after the acute phase, posthemorrhagic hydrocephalus is a long-term complication, frequently requiring permanent ventriculoperitoneal shunt (VPS) placement. Currently, there are no risk classification methods integrating the constellation of clinical data to predict short- and long-term prognosis in neonatal IVH. To address this need, the authors developed a two-part machine learning approach for predicting short- and long-term outcomes after diagnosis of neonatal IVH. Integrating both maternal and neonatal characteristics, they developed a binary classifier to predict short-term mortality risk and a clinical scale to predict the long-term risk of VPS placement. METHODS Neonates with IVH were identified from the Optum Clinformatics Data Mart administrative claims database. Matched maternal and childbirth characteristics were obtained for all patients. The primary endpoints of interest were short-term (30 day) mortality and long-term VPS placement. Classification of short-term mortality risk was evaluated using 5 different machine learning approaches and the best-performing method was validated using a withheld validation subset. Prediction of long-term shunt risk was performed using a multivariable Cox regression model with stepwise variable selection, which was subsequently converted to an easily applied integer risk scale. RESULTS A total of 5926 neonates with IVH were identified. Most patients were born before 32 weeks’ gestation (67.2%) and with low birth weight (81.2%). Empirical 30-day mortality risk was 10.9% across all IVH grades and highest among grade IV IVH (34.3%). Among the neonates who survived > 30 days, actuarial 12-month postdiagnosis risk of shunt placement was 5.4% across all IVH grades and 31.3% for grade IV IVH. The optimal short-term risk classifier was a random forest model achieving an area under the receiver operating characteristic curve of 0.882 with important predictors ranging from gestational age to diverse comorbid medical conditions. Selected features for long-term shunt risk stratification were IVH grade, respiratory distress syndrome, disseminated intravascular coagulation, and maternal preeclampsia or eclampsia. An integer risk scale, termed the Shunt Prediction After IVH in Neonates (SPAIN) scale, was developed from these 4 features, which, evaluated on withheld cases, demonstrated improved risk stratification compared with IVH grade alone (Harrell’s concordance index 0.869 vs 0.852). CONCLUSIONS In a large cohort of neonates with IVH, the authors developed a two-pronged, integrated, risk classification approach to anticipate short-term mortality and long-term shunt risk. The application of such approaches may improve the prognostication of outcomes and identification of higher-risk individuals who warrant careful surveillance and early intervention.

Background There is a lack of literature guiding treatment of giant cell glioblastoma (gcGBM), a rare subtype of glioblastoma (GBM). We used a national hospital-based registry to explore treatment patterns and outcomes associated with gcGBM. Methods Adult patients (age ≥18 years) diagnosed with gcGBM or GBM between 2004 and 2014 were identified from the National Cancer Database. χ2 analysis and Wilcoxon rank sum testing were used to compare characteristics between the gcGBM and GBM cohorts. Kaplan-Meier statistics, univariable and multivariable Cox regression, and propensity score matching were used to evaluate association between patient, tumor and treatment factors, and survival outcomes. Correlation analysis was used to evaluate historical trends in the treatment of gcGBM. Landmark analysis allowed for accounting of immortal time. Results In total, 683 patients with gcGBM were identified. Patients with gcGBM had improved survival compared with patients with GBM (15.5 months from landmark vs. 11.7; P $63,000 (P = 0.004) predisposed patients to improved outcomes. Patients receiving trimodal therapy (biopsy and/or surgery, radiotherapy, and chemotherapy) experienced better outcomes compared with those receiving either biopsy and/or surgery only or biopsy and/or surgery and radiotherapy without systemic therapy (median survival, 17.55 months vs. 6.68 months; P Conclusions gcGBM has favorable prognosis compared with GBM and should be aggressively managed with trimodal therapy. Prospective studies of gcGBM are warranted to better characterize gcGBM treatment outcomes.

Objective In the wake of the COVID-19 pandemic, the Centers for Medicare & Medicaid Services (CMS) has recommended the temporary cessation of all elective surgeries. The effects on patients' interest of elective neurosurgical procedures are currently unexplored. Methods Using Google Trends, search terms of 7 different neurosurgical procedure categories (trauma, spine, tumor, movement disorder, epilepsy, endovascular, and miscellaneous) were assessed in terms of relative search volume (RSV) between January 2015 and September 2020. Analyses of search terms were performed for over the short term (February 18, 2020, to April 18, 2020), intermediate term (January 1, 2020, to May 31, 2020), and long term (January 2015 to September 2020). State-level interest during phase I reopening (April 28, 2020, to May 31, 2020) was also evaluated. Results In the short term, RSVs of 4 categories (epilepsy, movement disorder, spine, and tumor) were significantly lower in the post-CMS announcement period. In the intermediate term, RSVs of 5 categories (miscellaneous, epilepsy, movement disorder, spine, and tumor) were significantly lower in the post-CMS announcement period. In the long term, RSVs of nearly all categories (endovascular, epilepsy, miscellaneous, movement disorder, spine, and tumor) were significantly lower in the post-CMS announcement period. Only the movement disorder procedure category had significantly higher RSV in states that reopened early. Conclusions With the recommendation for cessation of elective surgeries, patient interests in overall elective neurosurgical procedures have dropped significantly. With gradual reopening, there has been a resurgence in some procedure types. Google Trends has proven to be a useful tracker of patient interest and may be used by neurosurgical departments to facilitate outreach strategies.

We set to identify prognostic factors in a retrospective cohort of consecutive patients with stage I-II diffuse large B-cell lymphoma treated with rituximab-chemotherapy with or without radiotherapy from 2001 through 2017 at our institution. We identified 143 patients with median follow-up of 7.7 years. The majority were male (59.4%), had stage II (53.1%), had stage-modified IPI 0-1 (smIPI, 58.1%), and had non-bulky disease (7 cm, 68.5%). 99 patients (69.2%) received rituximab-chemotherapy followed by radiotherapy, and 44 patients (30.8%) received rituximab-chemotherapy alone. The 5-year progression-free survival (PFS) and overall survival (OS) were 81.2% and 88.9%, respectively. The 5-year PFS for those with smIPI 0-1 versus 2-4 was 89.5% versus 69.7%, respectively (

To describe opioid stewardship in ambulatory otologic surgery from 2005 to 2017.Descriptive study of US private insurance claims.Nationwide deidentified private insurance claims database (Clinformatics DataMart; Optum).A total of 17,431 adult opioid-naïve outpatients were included in the study. Patients were identified fromThe mean prescribed perioperative dose over the examined period was 203.03 MMEs (95% CI, 200.27-205.79; 5-mg hydrocodone pill equivalents, 40.61). In multivariate analysis, patients undergoing mastoid surgery were prescribed more opioids than those undergoing middle ear surgery (mean difference, 39.89 MME [95% CI, 34.37-45.41],While the amount of opioids prescribed perioperatively has declined in recent years, otologists should continue to be cognizant of potential overprescribing in light of previous studies of patients' relatively low opioid intake.

PURPOSE Patients with Diffuse Large B-cell Lymphoma (DLBCL) in need of immediate therapy are largely under-represented in clinical trials. The diagnosis-to-treatment interval (DTI) has recently been described as a metric to quantify such patient selection bias, with short DTI being associated with adverse risk factors and inferior outcomes. Here, we characterized the relationships between DTI, circulating tumor DNA (ctDNA), conventional risk factors, and clinical outcomes, with the goal of defining objective disease metrics contributing to selection bias. PATIENTS AND METHODS We evaluated pretreatment ctDNA levels in 267 patients with DLBCL treated across multiple centers in Europe and the United States using Cancer Personalized Profiling by Deep Sequencing. Pretreatment ctDNA levels were correlated with DTI, total metabolic tumor volumes (TMTVs), the International Prognostic Index (IPI), and outcome. RESULTS Short DTI was associated with advanced-stage disease ( P < .001) and higher IPI ( P < .001). We also found an inverse correlation between DTI and TMTV ( RS = −0.37; P < .001). Similarly, pretreatment ctDNA levels were significantly associated with stage, IPI, and TMTV (all P < .001), demonstrating that both DTI and ctDNA reflect disease burden. Notably, patients with shorter DTI had higher pretreatment ctDNA levels ( P < .001). Pretreatment ctDNA levels predicted short DTI independent of the IPI ( P < .001). Although each risk factor was significantly associated with event-free survival in univariable analysis, ctDNA level was prognostic of event-free survival independent of DTI and IPI in multivariable Cox regression (ctDNA: hazard ratio, 1.5; 95% CI [1.2 to 2.0]; IPI: 1.1 [0.9 to 1.3]; −DTI: 1.1 [1.0 to 1.2]). CONCLUSION Short DTI largely reflects baseline tumor burden, which can be objectively measured using pretreatment ctDNA levels. Pretreatment ctDNA levels therefore have utility for quantifying and guarding against selection biases in prospective DLBCL clinical trials.

Both artificial intelligence (AI) and clinical data acquisition are advancing at a rapid pace, making this an exciting time as clinicians and computer scientists collaborate to develop automated tools for understanding disease pathophysiology and improving patient care. The development of machine learning algorithms specific to pediatric diseases may help compensate for the pediatric evidence gap as well as the lack of pediatric subspecialists outside of major tertiary care centers. In this chapter, we review early efforts and ongoing advances in applying AI to pediatric disease diagnosis, prognosis, and management. Specifically we discuss studies addressing prematurity, childhood brain tumors, epilepsy, autism spectrum disorder, mood and psychotic disorders, hydrocephalus, traumatic brain injury, and other entities. We highlight the ongoing transition of clinical pediatrics into an increasingly computer-assisted field and discuss challenges and opportunities for growth in this arena.

7565 Background: Detection of circulating tumor DNA (ctDNA) has prognostic value in diverse tumors, including DLBCL. Despite uses for assessing molecular response to therapy, current methods using immunoglobulin or hybrid-capture sequencing have suboptimal sensitivity, particularly when disease-burden is low. This contributes to a high false negative rate at key milestones such as at the end of therapy (EOT; Kumar A, ASH 2020). We explored the utility of detecting multiple mutations (phased variants, PVs) on individual cell-free DNA (cfDNA) strands to improve MRD in DLBCL. Methods: We applied Phased Variant Enrichment and Detection Sequencing to track PVs from 485 specimens from 117 DLBCL patients undergoing first-line therapy. We sequenced cfDNA prior to, during, and after therapy to assess the prognostic value of MRD. We compared the performance of PhasED-Seq to current techniques, including SNV-based CAPP-Seq and duplex sequencing. Results: To establish its detection limit for ctDNA, we compared the background error-profile of of PVs and SNVs in cfDNA sequencing from healthy subjects. PV-detection by PhasED-Seq demonstrated a lower background profile than SNVs, even when considering duplex molecules (n = 12; 8.0e-7 vs 3.3e-5 and 1.2e-5; P < 0.0001). We also assessed analytical sensitivity within a ctDNA limiting dilution series from 3 patients, simulating tumor fractions from 0.1% to 0.00005% (1:2,000,000). PhasED-Seq outperformed SNV-based methods and duplex sequencing for recovery of expected tumor content below 0.01% (P < 0.0001 and P = 0.005 respectively by paired t-test). We then explored disease detection in clinical samples. We identified SNVs and PVs from pretreatment tumor or plasma and followed these variants in serial cfDNA. Using SNV-based methods, 40% and 59% of patients had undetectable ctDNA after 1 or 2 cycles (n = 82 and 88). However, 24% and 25% of these cases had detectable ctDNA by PhasED-Seq. Importantly, MRD detection by PhasED-Seq was prognostic for event-free survival even in patients with undetectable ctDNA by SNVs. We next explored the utility of PhasED-Seq at the EOT in 19 subjects, 5 of whom experienced eventual disease progression. While only 2/5 cases with progression had detectable disease at EOT using SNVs, PhasED-Seq detected all 5/5 cases. PhasED-Seq also correctly identified all patients (14/14) without clinical relapse as having no residual disease, including one patient who discontinued therapy after 1 cycle due to toxicity, but remains in remission > 5 years after this single treatment. This resulted in superior classification of patients for EFS using PVs compared with SNVs (C-statistic: 0.98 vs 0.60, P = 0.02). Conclusions: Tracking PVs results in significantly lower background rates than SNV-based approaches, enabling detection to parts per million range. PhasED-Seq improves on disease detection in DLBCL at the EOT, allowing possible MRD-driven consolidative approaches.