Using a forward genetics ENU mutagenesis screen for recessive mutations that affect circadian rhythmicity in the mouse, we isolated a long period (approximately 26 hr) circadian mutant named Overtime (Ovtm). Positional cloning and genetic complementation reveal that Ovtm is encoded by the F-box protein FBXL3, a component of the SKP1-CUL1-F-box-protein (SCF) E3 ubiquitin ligase complex. The Ovtm mutation causes an isoleucine to threonine (I364T) substitution leading to a loss of function in FBXL3, which interacts specifically with the CRYPTOCHROME (CRY) proteins. In Ovtm mice, expression of the PERIOD proteins PER1 and PER2 is reduced; however, the CRY proteins CRY1 and CRY2 are unchanged. The loss of FBXL3 function leads to a stabilization of the CRY proteins, which in turn leads to a global transcriptional repression of the Per and Cry genes. Thus, Fbxl3(Ovtm) defines a molecular link between CRY turnover and CLOCK/BMAL1-dependent circadian transcription to modulate circadian period.

Objectives Postoperative readmission impacts patient care and healthcare costs. There is a paucity of nation-wide data describing the clinical significance of readmission following thoracic operations. The purpose of this study was to evaluate the relationship between postoperative readmission and mortality following lung cancer resection. Methods Data were extracted for lung cancer resection patients from the linked SEER-Medicare registry (2006-2011), including demographics, comorbidities, socioeconomic factors, readmission within 30 days from discharge, and 90-day mortality. Readmitting facility and diagnoses were identified. A hierarchical regression model clustered at the hospital level identified predictors of readmission. Results We identified 11,432 lung cancer resection patients discharged alive from 677 hospitals. The median age was 74.5 years and 52% of patients received an open lobectomy. 30-day readmission rate was 12.8%, and 28.3% of readmissions were to facilities that did not perform the original operation. Readmission was associated with a six-fold increase in 90-day mortality (14.4% vs. 2.5%, p <0.001). The most common readmitting diagnoses were respiratory insufficiency, pneumonia, pneumothorax, and cardiac complications. Patient factors associated with readmission included resection type, age, prior induction chemoradiation, preoperative comorbidities including congestive heart failure and COPD, and low regional population density. Conclusions Factors associated with early readmission following lung cancer resection include patient comorbidities, type of operation, and socioeconomic factors. Metrics that only report readmissions to the operative provider miss one-fourth of all cases. Importantly, readmitted patients have an increased risk of death and demand maximum attention and optimal care.

Improved statistical practice is needed when using propensity scoring. This article suggests standard criteria for using this method in Journal publications.

BACKGROUND The purpose of this study is to compare the compositions of federally-funded surgical research between 2003 and 2013, and to assess differences in funding trends between surgery and other medical specialties. DATA SOURCES The NIH RePORTER database was queried for grants within core surgical disciplines during 2003 and 2013. Funding was categorized by award type, methodology, and discipline. Application success rates for surgery and five non-surgical departments were trended over time. RESULTS Inflation-adjusted NIH funding for surgical research decreased 19% from $270M in 2003 to $219M in 2013, with a shift from R-awards to U-awards. Proportional funding to outcomes research almost tripled, while translational research diminished. Non-surgical departments have increased NIH application volume over the last 10 years; however, surgery’s application volume has been stagnant. CONCLUSIONS To preserve surgery’s role in innovative research, new efforts are needed to incentivize an increase in application volume.

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Background Postoperative mortality is the most commonly reported surgical quality measure. However, such metrics may be incapable of identifying performance outliers. The purpose of this study was to compare different measures of postoperative mortality following lung cancer resection using a large multi-institutional database. Methods Data were extracted for lung cancer resection patients from the linked SEER-Medicare registry (2006–2010) which provides detailed and longitudinal information about Medicare beneficiaries with cancer. Four definitions of postoperative mortality were evaluated: in-hospital, 30-day, perioperative and 90-day. Hierarchical regression models were used to estimate mortality risk at 30 and 90 days, and provider quality was assessed by comparing observed versus expected mortality. Results We identified 11,787 lung cancer resection patients from 686 hospitals. The median age was 74 years and 52% of patients were treated with open lobectomy. While 30-day, perioperative and in-hospital mortality rates were between 3–4%, 90-day mortality was almost double (6.89%). Clinical variables associated with 90-day mortality included gender, preexisting comorbidities, and procedure type. There were no statistically-significant differences in 30- or 90-day mortality among providers. Conclusions Currently-reported measures of in-hospital and 30-day postoperative mortality do not adequately represent a patient’s true mortality risk as mortality almost doubles by 90-days. Due to low occurrence rate and variable provider volumes, neither 30- nor 90-day mortality are suitable quality indicators for lung resection.

Objectives Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is becoming the preferred method of mediastinal staging for lung cancer. We investigated the learning curve for EBUS-TBNA using risk-adjusted cumulative sum (Cusum). Methods A retrospective study of EBUS-TBNA was performed at a single academic institution for patients with mediastinal or hilar lymphadenopathy in the setting of proven or suspected lung cancer. A sampling pass was defined as a full retraction and repositioning of the aspiration needle. Rapid on-site evaluation was not available. To track proficiency, risk-adjusted Cusum analysis was performed using acceptable and unacceptable failure rates of 10% and 20%, respectively. Failure was defined as false negative or nondiagnostic results. Results During the study period, 231 patients underwent EBUS-TBNA. Prevalence of mediastinal or hilar malignancy was 66.7% (154 out of 231). Sensitivity was 92.2% (142 out of 154), and negative predictive value was 87.9% (58 out of 66). Node size was identified as a significant predictor of EBUS-TBNA success by multiple regression. Risk-adjusted Cusum analysis demonstrated that the first and only unacceptable decision interval was crossed at 22 cases. Individual practitioner learning curves were highly variable, and the operator with the highest volume was the most consistently proficient. Conclusions In our experience, attainment of an acceptable failure rate for EBUS-TBNA required 22 cases. Node size is a predictor of EBUS-TBNA success. Risk-adjusted Cusum proved a powerful evaluative tool to monitor the training process of this new procedure.

Introduction Infiltration of non-small-cell lung cancer (NSCLC) by CD8+ T lymphocytes predicts improved patient survival; however, heterogeneity of intratumoral localization complicates this assessment. Strategies for tumor sampling may not accurately represent the whole tumor. We hypothesized that sampling strategies may alter the identification of tumors with high CD8 density and affect the prognostic significance. Patients and methods Twenty-three primary NSCLC tumors were immunohistochemically stained for CD8 and were assessed using automated software with eight different sampling strategies or the whole tumor. Results of all sampling strategies were compared to the whole tumor counts (paired t tests, Pearson’s r). Associations between CD8 densities and overall survival were assessed (log-rank test). Results Counts from all eight sampling strategies significantly correlated with whole tumor counts (p ≤ 0.001). However, the magnitude of CD8+ cell counts and categorization into high vs low infiltrate groups were affected by the sampling strategy. The most concordant values were derived from random sampling of 20 % of the tumor, a simulated core biopsy, or from sampling the tumor center. TIL infiltration was associated with survival when sampling the center (p = 0.038), but not the invasive margin (p > 0.2) or other strategies. Conclusion Different tumor sampling strategies may yield discordant TIL density results and different stratification for risk assessment. Small biopsies may be particularly unrepresentative. Random sampling of larger tumor areas is recommended. Enumerating CD8+ T cells in the tumor center may have prognostic value.