Correlation of Bronchoscopy and CT in Characterizing Malignant Central Airway Obstruction.

BACKGROUND: Malignant Central Airway Obstruction (MCAO) presents a significant challenge in lung cancer management, with notable morbidity and mortality implications. While bronchoscopy is the established diagnostic standard for confirming MCAO and assessing obstruction subtype (intrinsic, extrinsic, mixed) and severity, Computed Tomography (CT) serves as an initial screening tool. However, the extent of agreement between CT and bronchoscopy findings for MCAO remains unclear. METHODS: To assess the correlation between bronchoscopy and CT, we conducted a retrospective review of 108 patients at Roswell Park Comprehensive Cancer Center, analyzing CT and bronchoscopy results to document MCAO presence, severity, and subtype. RESULTS: CT correctly identified MCAO in 99% of cases (107/108). Agreement regarding obstruction subtype (80.8%, Cohen's κ = 0.683, p < 0.001), and severity (65%, Quadratic κ = 0.657, p < 0.001) was moderate. CT tended to equally overestimate (7/19) and underestimate (7/19) the degree of obstruction. CT was also poor in identifying mucosal involvement in mixed MCAO. CONCLUSIONS: CT demonstrates reasonable agreement with bronchoscopy in detecting obstruction. Nevertheless, when CT indicates a positive finding for MCAO, it is advisable to conduct bronchoscopy. This is because CT lacks reliability in determining the severity of obstruction and identifying the mucosal component of mixed disease.

A survey of surveys: an evaluation of the quality of published surveys in neurosurgery.

PURPOSE: Surveys generate valuable data in epidemiologic and qualitative clinical research. The quality of a survey depends on its design, the number of responses it receives, and the reporting of the results. In this study, we aimed to assess the quality of surveys in neurosurgery. METHODS: Neurosurgical surveys published between 2000 and 2020 (inclusive) were identified from PubMed. Various datapoints regarding the surveys were collated. The number of citations received by the papers was determined from Google Scholar. A 6-dimensional quality assessment tool was applied to the surveys. Parameters from this tool were combined with the number of responses received to create the survey quality score (SQS). RESULTS: A total of 618 surveys were included for analysis. The target sample size correlated with the number of responses received. The response rate correlated positively with the target sample size and the number of reminders sent and negatively with the number of questions in the survey. The median number of authors on neurosurgery survey papers was 6. The number of authors correlated with the SQS and the number of citations received by published survey papers. The median normalized SQS for neurosurgical surveys was 65%. The nSQS independently predicted the citations received per year by surveys. CONCLUSIONS: The modifiable factors that correlated with improvements in survey design were optimizing the number of questions, maximizing the target sample size, and incorporating reminders in the survey design. Increasing the number of contributing authors led to improvements in survey quality. The SQS was validated and correlated well with the citations received by surveys.

Neoadjuvant therapy in non-small cell lung cancer: basis, promise, and challenges.

Introduction: Survival rates for early-stage non-small cell lung cancer (NSCLC) remain poor despite the decade-long established standard of surgical resection and systemic adjuvant therapy. Realizing this, researchers are exploring novel therapeutic targets and deploying neoadjuvant therapies to predict and improve clinical and pathological outcomes in lung cancer patients. Neoadjuvant therapy is also increasingly being used to downstage disease to allow for resection with a curative intent. In this review, we aim to summarize the current and developing landscape of using neoadjuvant therapy in the management of NSCLC. Methods: The PubMed.gov and the ClinicalTrials.gov databases were searched on 15 January 2023, to identify published research studies and trials relevant to this review. One hundred and seven published articles and seventeen ongoing clinical trials were selected, and relevant findings and information was reviewed. Results & Discussion: Neoadjuvant therapy, proven through clinical trials and meta-analyses, exhibits safety and efficacy comparable to or sometimes surpassing adjuvant therapy. By attacking micro-metastases early and reducing tumor burden, it allows for effective downstaging of disease, allowing for curative surgical resection attempts. Research into neoadjuvant therapy has necessitated the development of surrogate endpoints such as major pathologic response (MPR) and pathologic complete response (pCR) allowing for shorter duration clinical trials. Novel chemotherapy, immunotherapy, and targeted therapy agents are being tested at a furious rate, paving the way for a future of personalized systemic therapy in NSCLC. However, challenges remain that prevent further mainstream adoption of preoperative (Neoadjuvant) therapy. These include the risk of delaying curative surgical resection in scenarios of adverse events or treatment resistance. Also, the predictive value of surrogate markers of disease cure still needs robust verification. Finally, the body of published data is still limited compared to adjuvant therapy. Addressing these concerns with more large scale randomized controlled trials is needed.

Obesity and lung cancer-a narrative review.

Background and Objective: A highly nuanced relationship exists between obesity and lung cancer. The association between obesity and lung cancer risk/prognosis varies depending on age, gender, race, and the metric used to quantify adiposity. Increased body mass index (BMI) is counterintuitively associated with decreased lung cancer incidence and mortality, giving rise to the term 'obesity paradox'. Potential explanations for this paradox are BMI being a poor measure of obesity, confounding by smoking and reverse causation. A literature search of this topic yields conflicting conclusions from various authors. We aim to clarify the relationship between various measures of obesity, lung cancer risk, and lung cancer prognosis. Methods: The PubMed database was searched on 10 August 2022 to identify published research studies. Literature published in English between 2018 and 2022 were included. Sixty-nine publications were considered relevant, and their full text studied to collate information for this review. Key Content and Findings: Lower lung cancer incidence and better prognosis was associated with increased BMI even after accounting for smoking and pre-clinical weight loss. Individuals with high BMI also responded better to treatment modalities such as immunotherapy compared to individuals with a normal BMI. However, these associations varied highly depending on age, gender, and race. Inability of BMI to measure body habitus is the main driver behind this variability. The use of anthropometric indicators and image-based techniques to quantify central obesity easily and accurately is on the rise. Increase in central adiposity is associated with increased incidence and poorer prognosis of lung cancer, contrasting BMI. Conclusions: The obesity paradox may arise due to the improper use of BMI as a measure of body composition. Measures of central obesity better portray the deleterious effects of obesity and are more appropriate to be discussed when talking about lung cancer. The use of obesity metrics based on anthropometric measurements and imaging modalities has been shown to be feasible and practical. However, a lack of standardization makes it difficult to interpret the results of studies using these metrics. Further research must be done to understand the association between these obesity metrics and lung cancer.

The Author-Level Metrics Study: An Analysis of the Traditional and Alternative Metrics of Scholarly Impact for Neurosurgical Authors.

Background and objective There is a paucity of information regarding the concordance of traditional metrics across publicly searchable databases and about the correlation between alternative and traditional metrics for neurosurgical authors. In this study, we aimed to assess the congruence between traditional metrics reported across Google Scholar (GS), Scopus (Sc), and ResearchGate (RG). We also aimed to establish the mathematical correlation between traditional metrics and alternative metrics provided by ResearchGate. Methods Author names listed on papers published in the Journal of Neurosurgery (JNS) in 2019 were collated. Traditional metrics [number of publications (NP), number of citations (NC), and author H-indices (AHi)] and alternative metrics (RG score, Research Interest score, etc. from RG and the GS i10-index) were also collected from publicly searchable author profiles. The concordance between the traditional metrics across the three databases was assessed using the intraclass correlation coefficient and Bland-Altman (BA) plots. The mathematical relation between the traditional and alternative metrics was analyzed. Results The AHi showed excellent agreement across the three databases studied. The level of agreement for NP and NC was good at lower median counts. At higher median counts, we found an increase in disagreement, especially for NP. The RG score, number of followers on RG, and Research Interest score independently predicted NC and AHi with a reasonable degree of accuracy. Conclusions A composite author-level matrix with AHi, RG score, Research Interest score, and the number of RG followers could be used to generate an "Impact Matrix" to describe the scholarly and real-world impact of a clinician's work.