An assessment of the correlation between robust CT-derived ventilation and pulmonary function test in a cohort with no respiratory symptoms

Objective:To evaluate CT-ventilation imaging (CTVI) within a well-characterized, healthy cohort with no respiratory symptoms and examine the correlation between CTVI and concurrent pulmonary function test (PFT).Methods:CT scans and PFTs from 77 Caucasian participants in the NORM dataset (clinicaltrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00848406","term_id":"NCT00848406"}}NCT00848406) were analyzed. CTVI was generated using the robust Integrated Jacobian Formulation (IJF) method. IJF estimated total lung capacity (TLC) was computed from CTVI. Bias-adjusted Pearson’s correlation between PFT and IJF-based TLC was computed.Results:IJF- and PFT-measured TLC showed a good correlation for both males and females [males: 0.657, 95% CI (0.438–0.797); females: 0.667, 95% CI (0.416–0.817)]. When adjusting for age, height, smoking, and abnormal CT scan, correlation moderated [males: 0.432, 95% CI (0.129–0.655); females: 0.540, 95% CI (0.207–0.753)]. Visual inspection of CTVI revealed participants who had functional defects, despite the fact that all participant had normal high-resolution CT scan.Conclusion:In this study, we demonstrate that IJF computed CTVI has good correlation with concurrent PFT in a well-validated patient cohort with no respiratory symptoms.Advances in knowledge:IJF-computed CTVI’s overall numerical robustness and consistency with PFT support its potential as a method for providing spatiotemporal assessment of high and low function areas on volumetric non-contrast CT scan.     

A literature-based treatment algorithm for low-grade neuroendocrine liver metastases

BackgroundThe optimal timing of treatment of liver metastases from low-grade neuroendocrine tumors (LG-NELM) varies significantly due to numerous treatment modalities and the literature supporting various treatment(s). This study sought to create and validate a literature-based treatment algorithm for LG-NELM.MethodsA treatment algorithm to maximize overall survival (OS) was designed using peer-reviewed articles evaluating treatment of LG-NELM. This algorithm was retrospectively applied to patients treated for LG-NELM at our institution. Deviation was determined based on whether or not a patient received treatment consistent with that recommended by the algorithm. Patients who did and did not deviate from the algorithm were compared with respect to OS and number of treatments.ResultsApplying our algorithm to a 149-patient cohort, 57 (38%) deviated from recommended treatment. Deviation occurred in the form of alternative (28, 49%) versus additional procedures (29, 51%). Algorithm deviators underwent significantly more procedures than non-deviators (median 1 vs. 2, p < 0.001). Cox model indicated no difference in OS associated with algorithm deviation (HR 1.19, p = 0.58) when controlling for age and tumor characteristics.ConclusionThis literature-based algorithm helps standardize treatment protocols in patients with LG-NELM and can reduce cost and risk by minimizing unnecessary procedures. Prospective implementation and validation is required.     

Time-varying prognostic value of primary tumor sidedness in metastatic colorectal cancer: A population-based study and meta-analysis

We studied the prognostic value of primary tumor sidedness in metastatic colorectal cancer over time and across treatment lines. Population data on synchronous metastatic colorectal cancer patients were extracted from the Netherlands Cancer Registry and SEER database. Pubmed, EMBASE and Cochrane library were searched for prospective studies on metastatic colorectal cancer to conduct a meta-analysis. Inclusion criteria consisted of metastatic disease, systemic treatment with palliative intent and specification of primary tumor location. Data were pooled using a random-effects model. For the population-based data, multivariable Cox models were constructed. The Grambsch-Therneau test was conducted to evaluate the potential time-varying nature of sidedness. Meta-regression incorporating treatment-line as variable was conducted to test the pre-specified hypothesis that the prognostic value of sidedness varies over time. Analysis of 12 885 and 16 160 synchronous metastatic colorectal cancer patients registered in the Netherlands Cancer Registry and SEER database, respectively, indicated a time-varying prognostic value of sidedness (P < .01). Thirty-one studies were selected for the meta-analysis (9558 patients for overall survival analysis). Pooled univariable hazard ratio_{left-sided/right-sided} for overall survival was 0.71 (95% CI: 0.65-0.76) in 1st-line, 0.76 (0.54-1.06) in 2nd-line and 1.01 (0.86-1.19) in 3rd-line studies. Hazard ratios were significantly influenced by treatment line (P = .035). The prognostic value of sidedness of the primary tumor in metastatic colorectal cancer patients treated with palliative systemic therapy decreases over time since diagnosis, suggesting that sidedness may not be a useful stratification factor in late-line trials. This decrease in prognostic value should be taken into account when providing prognostic information to patients.     

The social vulnerability metric (SVM) as a new tool for public health

Objective

To derive and validate a new ecological measure of the social determinants of health (SDoH), calculable at the zip code or county level.

Data Sources and Study Setting

The most recent releases of secondary, publicly available data were collected from national U.S. health agencies as well as state and city public health departments.

Study Design

The Social Vulnerability Metric (SVM) was constructed from U.S. zip-code level measures (2018) from survey data using multidimensional Item Response Theory and validated using outcomes including all-cause mortality (2016), COVID-19 vaccination (2021), and emergency department visits for asthma (2018). The SVM was also compared with the existing Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) to determine convergent validity and differential predictive validity.

Data Collection/Extraction Methods

The data were collected directly from published files available to the public online from national U.S. health agencies as well as state and city public health departments.

Principal Findings

The correlation between SVM scores and national age-adjusted county all-cause mortality was r = 0.68. This correlation demonstrated the SVM's robust validity and outperformed the SVI with an almost four-fold increase in explained variance (46% vs. 12%). The SVM was also highly correlated (r ≥ 0.60) to zip-code level health outcomes for the state of California and city of Chicago.

Conclusions

The SVM offers a measurement tool improving upon the performance of existing SDoH composite measures and has broad applicability to public health that may help in directing future policies and interventions. The SVM provides a single measure of SDoH that better quantifies associations with health outcomes.