Ranking NIH Funding of Surgical Departments Based Upon a Modified Index.

BACKGROUND: The Blue Ridge Institute for Medical Research (BRIMR) reports a ranking of surgical department NIH funding each fiscal year based on more than 41,000 individual investigators. This report is used to measure the research productivity of the faculty or department. However, this method includes institutional grants awarded to Cancer Centers or Centers for Research, which do not reflect individual or departmental research. To measure the research productivity of a surgical department more directly, we created a modified BRIMR index excluding grants to cancer or research centers. We evaluated how our modified index of surgical departments compared to the rankings by BRIMR. METHODS: Publicly available BRIMR data was filtered for all grants awarded to principal investigators in a surgical department within a medical school. All funding for Cancer Centers or Centers for Research was excluded. The remaining grants were totaled, producing a new ranking of surgical departments. RESULTS: After excluding $42,761,752 in grants to Cancer Centers and Centers for Research, there was individual movement of 33 surgical departments on the ranking list. However, only four departments moved either up or down one quartile. No surgical department moved 2 or more quartiles. CONCLUSIONS: NIH funding for Cancer Centers and Centers for Research comprised 10% of all NIH funding for medical school-associated surgical departments. Exclusion of this funding resulted in no significant change within surgical department quartile rankings. This suggests the BRIMR measure of research productivity does not need modification.

Integrated Biomarkers for the Management of Indeterminate Pulmonary Nodules.

Rationale: Patients with indeterminate pulmonary nodules (IPNs) at risk of cancer undergo high rates of invasive, costly, and morbid procedures. Objectives: To train and externally validate a risk prediction model that combined clinical, blood, and imaging biomarkers to improve the noninvasive management of IPNs. Methods: In this prospectively collected, retrospective blinded evaluation study, probability of cancer was calculated for 456 patient nodules using the Mayo Clinic model, and patients were categorized into low-, intermediate-, and high-risk groups. A combined biomarker model (CBM) including clinical variables, serum high sensitivity CYFRA 21-1 level, and a radiomic signature was trained in cohort 1 (n = 170) and validated in cohorts 2-4 (total n = 286). All patients were pooled to recalibrate the model for clinical implementation. The clinical utility of the CBM compared with current clinical care was evaluated in 2 cohorts. Measurements and Main Results: The CBM provided improved diagnostic accuracy over the Mayo Clinic model with an improvement in area under the curve of 0.124 (95% bootstrap confidence interval, 0.091-0.156; P < 2 × 10-16). Applying 10% and 70% risk thresholds resulted in a bias-corrected clinical reclassification index for cases and control subjects of 0.15 and 0.12, respectively. A clinical utility analysis of patient medical records estimated that a CBM-guided strategy would have reduced invasive procedures from 62.9% to 50.6% in the intermediate-risk benign population and shortened the median time to diagnosis of cancer from 60 to 21 days in intermediate-risk cancers. Conclusions: Integration of clinical, blood, and image biomarkers improves noninvasive diagnosis of patients with IPNs, potentially reducing the rate of unnecessary invasive procedures while shortening the time to diagnosis.