Objective: Outcomes for lung cancer surgery are currently measured according to perioperative morbidity and mortality. However, the oncologic efficacy of the surgery is reflected by long-term survival. We examined correlation between measures of short-term and long-term performance for lung cancer surgery.
Methods: The Society of Thoracic Surgeons General Thoracic Surgery Database linked to Medicare survival data was queried for pathologic stage I lung cancer resected between 2009 and 2013. Two separate multivariable models were created: (1) short-term: avoidance of perioperative major morbidity and mortality; and (2) long-term: 3-year survival. Standardized incidence ratios were calculated for the Society of Thoracic Surgeons programs (participants) to determine risk-adjusted participant performance measures for the short- and long-term time points. Correlation of participant standardized incidence ratios for short- and long-term performance was assessed using the Pearson correlation coefficient.
Results: The study population included 12,596 patients from 229 participating programs. One hundred fifty-one participants met minimum volume and follow-up requirements for analysis. Overall, performance for the short-term measure was uniform with only 2 (1.3%) participants performing better than expected and 2 (1.3%) worse than expected. For the long-term measure, 9 (6%) participants achieved better than expected and 5 (3.3%) worse than expected survival. No participant was an above or below average performer for the short- and long-term measures. Further, no correlation was observed between participant short- and long-term performance (Pearson correlation coefficient, 0.12; 95% confidence interval, -0.04 to 0.28; P = .14).
Conclusions: Avoidance of perioperative morbidity and mortality is an incomplete measure of performance in lung cancer surgery. Lung cancer surgery performance metrics should assess the safety of surgery and long-term survival.
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http://dx.doi.org/10.1016/j.jtcvs.2018.09.141 | DOI Listing |
Ann Surg Oncol
January 2025
Department of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Sports Med Open
January 2025
Institute of Primary Care, University of Zurich, Zurich, Switzerland.
Background: Marathon training and running have many beneficial effects on human health and physical fitness; however, they also pose risks. To date, no comprehensive review regarding both the benefits and risks of marathon running on different organ systems has been published.
Main Body: The aim of this review was to provide a comprehensive review of the benefits and risks of marathon training and racing on different organ systems.
Nat Commun
January 2025
European Research Institute for the Biology of Ageing, University Medical Center Groningen, Groningen, Netherlands.
While the effect of amplification-induced oncogene expression in cancer is known, the impact of copy-number gains on "bystander" genes is less understood. We create a comprehensive map of dosage compensation in cancer by integrating expression and copy number profiles from over 8000 tumors in The Cancer Genome Atlas and cell lines from the Cancer Cell Line Encyclopedia. Additionally, we analyze 17 cancer open reading frame screens to identify genes toxic to cancer cells when overexpressed.
View Article and Find Full Text PDFCell Death Discov
January 2025
Institute of Biopharmaceutical Sciences, College of Pharmaceutical Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan.
TP53 mutations are recognized to correlate with a worse prognosis in individuals with non-small cell lung cancer (NSCLC). There exists an immediate necessity to pinpoint selective treatment for patients carrying TP53 mutations. Potential drugs were identified by comparing drug sensitivity differences, represented by the half-maximal inhibitory concentration (IC50), between TP53 mutant and wild-type NSCLC cell lines using database analysis.
View Article and Find Full Text PDFNat Commun
January 2025
Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA.
Recent barcoding technologies allow reconstructing lineage trees while capturing paired single-cell RNA-sequencing (scRNA-seq) data. Such datasets provide opportunities to compare gene expression memory maintenance through lineage branching and pinpoint critical genes in these processes. Here we develop Permutation, Optimization, and Representation learning based single Cell gene Expression and Lineage ANalysis (PORCELAN) to identify lineage-informative genes or subtrees where lineage and expression are tightly coupled.
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