To provide evidence-based recommendations to practicing clinicians on management of patients with stage III non-small-cell lung cancer (NSCLC).
An Expert Panel of medical oncology, thoracic surgery, ...radiation oncology, pulmonary oncology, community oncology, research methodology, and advocacy experts was convened to conduct a literature search, which included systematic reviews, meta-analyses, and randomized controlled trials published from 1990 through 2021. Outcomes of interest included survival, disease-free or recurrence-free survival, and quality of life. Expert Panel members used available evidence and informal consensus to develop evidence-based guideline recommendations.
The literature search identified 127 relevant studies to inform the evidence base for this guideline.
Evidence-based recommendations were developed to address evaluation and staging workup of patients with suspected stage III NSCLC, surgical management, neoadjuvant and adjuvant approaches, and management of patients with unresectable stage III NSCLC.Additional information is available at www.asco.org/thoracic-cancer-guidelines.
Salvage surgery refers to operative resection of persistent or recurrent disease in patients initially treated with intention‐to‐cure nonoperative management. In non‐small‐cell lung cancer, salvage ...surgery may be effective in treating selected patients with locally progressive tumors, recurrent local or locoregional disease, or local complications after nonoperative therapy. Importantly, those patients who may be candidates for salvage surgery are evolving, in terms of disease stage as well as the types of attempted definitive therapy received.
The Thoracic Surgery Social Media Network (TSSMN) is a collaborative effort of leading journals in cardiothoracic surgery to highlight publications via social media. This study aims to evaluate the ...1-year results of a prospective randomized social media trial to determine the effect of tweeting on subsequent citations and nontraditional bibliometrics.
A total of 112 representative original articles were randomized 1:1 to be tweeted via TSSMN or a control (non-tweeted) group. Measured endpoints included citations at 1 year compared with baseline, as well as article-level metrics (Altmetric score) and Twitter analytics. Independent predictors of citations were identified through univariable and multivariable regression analyses.
When compared with control articles, tweeted articles achieved significantly greater increase in Altmetric scores (Tweeted 9.4 ± 5.8 vs Non-tweeted 1.0 ± 1.8, P < .001), Altmetric score percentiles relative to articles of similar age from each respective journal (Tweeted 76.0 ± 9.1 percentile vs Non-tweeted 13.8 ± 22.7 percentile, P < .001), with greater change in citations at 1 year (Tweeted +3.1 ± 2.4 vs Non-Tweeted +0.7 ± 1.3, P < .001). Multivariable analysis showed that independent predictors of citations were randomization to tweeting (odds ratio OR 9.50; 95% confidence interval CI 3.30-27.35, P < .001), Altmetric score (OR 1.32; 95% CI 1.15-1.50, P < .001), open-access status (OR 1.56; 95% CI 1.21-1.78, P < .001), and exposure to a larger number of Twitter followers as quantified by impressions (OR 1.30, 95% CI 1.10-1.49, P < .001).
One-year follow-up of this TSSMN prospective randomized trial importantly demonstrates that tweeting results in significantly more article citations over time, highlighting the durable scholarly impact of social media activity.
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