Profiling Cell-Free DNA from Malignant Pleural Effusion for Oncogenic Driver Mutations in Patients with Treatment-Naive Stage IV Adenocarcinoma: A Multicenter Prospective Study.

INTRODUCTION: Comprehensive next-generation sequencing (NGS) of non-small-cell lung cancer specimens can identify oncogenic driver mutations and their corresponding targeted therapies. Plasma cell-free DNA (cfDNA) genotyping is easy to perform; however, false negatives cannot be overlooked. We explored malignant pleural effusion (MPE), a rich source of cfDNA, as a non-inferior alternative to tumor tissues for genotyping. METHODS: We conducted a prospective trial including 39 patients with newly diagnosed stage IV lung adenocarcinoma who presented with MPE. Tissue tests matching hotspot variants, including EGFR, ALK, and ROS1, were compared with the AlphaLiquid100 of PE-cfDNA. RESULTS: Among the 39 PE-cfDNA samples successfully sequenced, 32 (82.1%) had a PE cell-block tumor content of < 10%. Standard tissue or cell-block testing for EGFR, ALK, and ROS1 identified 20 mutations (51.3%), whereas PE cfDNA identified 25 mutations (64.1%). Five EGFR mutations were observed in PE cfDNA but not in Cobas EGFR owing to coverage or insufficient tumor content issues. The overall rate of oncogenic mutations identified in the PE cfDNA was 92.3%, and the mutation distribution was as follows: even with a very low cfDNA input, high detection rates could be achieved. Otherwise, most patients harbored co-mutations. Comparison of pleural fluid NGS with traditional testing revealed differences in accuracy. We also followed up with patients with EGFR-sensitizing mutations who had a treatment response rate of 97.2% after 3 months. CONCLUSIONS: Genotyping of MPE supernatant cfDNA is feasible in clinical practice, in addition to plasma and tumor testing, to improve diagnostic yield and extend patients' benefit from targeted therapies.

Translating Risk Ratios, Baseline Incidence, and Proportions Diseased to Correlations and Chi-Squared Statistics: Simulation Epidemiology.

Background In a population, when a disease is causing a symptom, the overall symptom incidence can be determined by proportions diseased, baseline symptom incidence, and risk ratios of developing the symptom due to the disease. There are various measures of association, including risk ratios. How risk ratios are linked to other measures of association, such as correlation coefficients and chi-squared statistics, has not been explicitly discussed. This study aims to demonstrate their connection via equations and simulations, assuming one disease causes symptoms. Methods The equations for correlation coefficients and chi-square statistics were rewritten using epidemiological measures: proportions diseased, baseline symptom incidence, and risk ratios. Simulations were conducted to test the accuracy of the equations. The baseline symptom incidence and the proportions diseased were assumed to be 0.05, 0.1, 0.2, 0.4, or 0.8. The risk ratios were assumed to be 0.5, 1, 2, 5, 10, and 25. Another disease that correlates with this disease was created (correlation = 0, 0.3, or 0.7). For each combination of symptom incidence, proportions diseased, risk ratios, and between-disease correlations, 10,000 subjects were simulated. The correlation coefficients and chi-squared statistics were approximated with epidemiologic measures and their interaction terms. R-squared was used to assess the importance of the epidemiologic measures. Results In the simulations, the overall symptom incidence, correlation coefficients, and chi-squared statistics between the disease and symptoms could be fully explained by the epidemiologic measures in the equations (R-squared = 1). When approximating correlation coefficients and chi-squared statistics with individual measures or their interaction terms, the importance of these measures depended on whether the at-risk incidence reached 1 or not. The numbers in the four cells in the contingency table predicted correlation coefficients, or chi-squared statistics, with different R-squared. Conclusion To our knowledge, this is the first study to translate the three epidemiologic measures (risk ratios, baseline symptom incidence, and proportions diseased) into correlation coefficients and chi-squared statistics. However, chi-squared statistics also depend on sample sizes. This study also provides a platform for developing teaching cases for students to investigate the causal relationship between diseases and symptoms or exposure and outcomes.

Mental Illness Diagnoses May Not Cause All Mental Symptoms: A Simulation Study for Major Depressive Episodes, Dysthymic Disorder, and Manic Episodes.

Objectives This study aims to understand the statistical significance of the associations between diagnoses and symptoms based on simulations that have been used to understand the interpretability of mental illness diagnoses. Methods The symptoms for the diagnosis of major depressive episodes, dysthymic disorder, and manic episodes were extracted from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR, American Psychiatric Association, Philadelphia, Pennsylvania). Without real-world symptom data, we simulated populations using various combinations of symptom prevalence and correlations. Assuming symptoms occurred with similar prevalence and correlations, for each combination of symptom prevalence (0.05, 0.1, 0.3, 0.5, and 0.7) and correlation (0, 0.1, 0.4, 0.7, and 0.9), 100 cohorts with 10,000 individuals were randomly created. Diagnoses were made according to the DSM-IV-TR criteria. The associations between the diagnoses and their input symptoms were quantified with odds ratios and correlation coefficients. P-values from 100 cohorts for each combination of symptom prevalence and correlation were summarized. Results Three mental illness diagnoses were not significantly correlated with their own symptoms in all simulations, particularly when symptoms were not correlated, except for the symptom in the major criteria of major depressive episodes or dysthymic disorder. The symptoms for the diagnosis of major depressive episodes and dysthymic disorder were significantly correlated with these two diagnoses in some simulations, assuming 0.1, 0.4, 0.7, or 0.9 symptom correlations, except for one symptom. The overlap in the input symptoms for the diagnosis of major depressive episodes and dysthymic disorder also leads to significant correlations between these two diagnoses, assuming 0.1, 0.4, 0.7, and 0.9 correlations between input symptoms. Manic episodes are not significantly associated with the input symptoms of major depressive episodes and dysthymic disorder. Conclusion There are challenges to establish the causation between psychiatric symptoms and mental illness diagnoses. There is insufficient prevalence and incidence data to show all psychiatric symptoms exist or can be observed in patients. The diagnostic accuracy of symptoms to detect a disease cause is far from perfect. Assuming the symptoms of three mood disorders may present in patients, three diagnoses are not significantly associated with all psychiatric symptoms used to diagnose them. The diagnostic criteria of the three diagnoses have not been designed to guarantee significant associations between symptoms and diagnoses. Because statistical associations are important for making causal inferences, there may be a lack of causation between diagnoses and symptoms. Previous research has identified factors that lead to insignificant associations between diagnoses and symptoms, including biases due to data processing and a lack of epidemiological evidence to support the design of mental illness diagnostic criteria.

Real world experience on the effectiveness and safety of pirfenidone in patients with idiopathic pulmonary fibrosis in Taiwan.

Introduction: Randomized controlled trials have demonstrated a reduction in the decline of lung function and a reduced risk of acute exacerbation in patients with idiopathic pulmonary fibrosis treated with the antifibrotic prifenidone. The present study aimed to investigate the real-world effectiveness and safety profile of pirfenidone treatment for patients with IPF in Taiwan. Methods: Between January 1, 2019 and December 31, 2020, we enrolled 50 patients who were newly diagnosed with IPF and had at least 12 months follow-up period after pirfenidone administration. Result: The primary outcome of pharmacologic effect showed that the mean differences in the absolute values of forced vital capacity from baseline were 0.2 liter (n = 36), 0.13 liter (n = 32), 0.04 liter (n = 26), and - 0.004 liter (n = 26) after 3, 6, 9, and 12 months of administration, respectively. A slight improvement in quality of life, including scores of chronic obstructive pulmonary disease assessment test and St. George's respiratory questionnaire scores. The most common adverse effects were gastrointestinal upset and dermatological problems. No new safety concerns were observed in the present study. Conclusion: Our real-world study describe for the first time in Taiwan, the use of pirfenidone over a 12 months period. This drug preserves the lung function and improves quality of life with tolerable side effects.

Factors associated with outcomes of second-line treatment for EGFR-mutant non-small-cell lung cancer patients after progression on first- or second-generation EGFR-tyrosine kinase inhibitor treatment.

Purpose: Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are standard first-line treatments for advanced EGFR-mutant non-small-cell lung cancer (NSCLC) patients. However, factors associated with outcomes after progression on first-line therapy are seldom investigated. Materials and methods: From January 2016 to December 2020, we enrolled 242 EGFR-mutant stage IIIB-IV NSCLC patients who progressed on first- or second-generation EGFR-TKI treatments, and 206 of them receive second-line treatments after disease progression. The factors that predict the survival outcomes of different second-line treatments after disease progression were evaluated. Clinical and demographic characteristics, including metastatic sites, neutrophil-to-lymphocyte ratio (NLR) at first-line progression, and second-line treatment regimens, and whether re-biopsied after disease progression or not, were reviewed for outcome analysis. Results: The univariate analysis showed that the PFS was shorted in male patients (p =0.049), patients with ECOG performance state ≥ 2 (p =0.014), former smokers (p =0.003), patients with brain metastasis (p =0.04), second-line chemotherapy or EGFR-TKIs other than osimertinib (p =0.002), and NLR ≥5.0 (p=0.024). In addition, second-line osimertinib was associated with longer OS compared to chemotherapy and other EGFR-TKI treatment (p =0.001). In the multivariate analysis, only second-line osimertinib was an independent predictor of PFS (p =0.023). Re-biopsy after first-line treatment was associated with a trend of better OS. Patients with NLR ≥5.0 at disease progression had shorter OS than patients with NLR <5.0 (p = 0.008). Conclusion: The benefits of osimertinib necessitate that aggressive re-biopsy after progression on first- or second-generation EGFR-TKI treatment is merited for appropriate second-line treatments to provide better outcomes for these patients.

The Upper Limits of Risk Ratios and Recommendations for Reporting Risk Ratios, Odds Ratios, and Rate Ratios.

Background Relative measures, including risk ratios (RRs) and odds ratios (ORs), are reported in many epidemiological studies. RRs represent how many times a condition is likely to develop when exposed to a risk factor. The upper limit of RRs is the multiplicative inverse of the baseline incidence. Ignoring the upper limits of RRs can lead to reporting exaggerated relative effect sizes. Objectives This study aims to demonstrate the importance of such upper limits for effect size reporting via equations, examples, and simulations and provide recommendations for the reporting of relative measures. Methods Equations to calculate RRs and their 95% confidence intervals (CIs) were listed. We performed simulations with 10,000 simulated subjects and three population variables: proportions at risk (0.05, 0.1, 0.3, 0.5, and 0.8), baseline incidence (0.05, 0.1, 0.3, 0.5, and 0.8), and RRs (0.5, 1.0, 5.0, 10.0, and 25.0). Subjects were randomly assigned with a risk based on the set of proportions-at-risk values. A disease occurred based on the baseline incidence among those not at risk. The incidence of those at risk was the product of the baseline incidence and the RRs. The 95% CIs of RRs were calculated according to Altman. Results The calculation of RR 95% CIs is not connected to the RR upper limits in equations. The RRs in the simulated populations at risk could reach the upper limits of RRs: multiplicative inverse of the baseline incidence. The upper limits to the derived RRs were around 1.25, 2, 3.3, 10, and 20, when the assumed baseline incidence rates were 0.8, 0.5, 0.3, 0.2, and 0.05, respectively. We demonstrated five scenarios in which the RR 95% CIs might exceed the upper limits. Conclusions Statistical significance does not imply the RR 95% CIs not exceeding the upper limits of RRs. When reporting RRs or ORs, the RR upper limits should be assessed. The rate ratio is also subject to a similar upper limit. In the literature, ORs tend to overestimate effect sizes. It is recommended to correct ORs that aim to approximate RRs assuming outcomes are rare. A reporting guide for relative measures, RRs, ORs, and rate ratios, is provided. Researchers are recommended to report whether the 95% CIs of relative measures, RRs, ORs, and rate ratios, overlap with the range of upper limits and discuss whether the relative measure estimates may exceed the upper limits.

Growth of Dunaliella viridis in multiple cycles of reclaimed media after repeated high pH-induced flocculation and harvesting.

Minimizing the use of water for growing microalgae is crucial for lowering the energy and costs of animal feed, food, and biofuel production from microalgae. Dunaliella spp., a haloterant species that can accumulate high intracellular levels of lipids, carotenoids, or glycerol can be harvested effectively using low-cost and scalable high pH-induced flocculation. However, the growth of Dunaliella spp. in reclaimed media after flocculation and the impact of recycling on the flocculation efficiency have not been explored. In this study, repeated cycles of growth of Dunaliella viridis in repeatedly reclaimed media from high pH-induced flocculation were studied by evaluating cell concentrations, cellular components, dissolved organic matter (DOM), and bacterial community shifts in the reclaimed media. In reclaimed media, D. viridis grew to the same concentrations of cells and intracellular components as fresh media-107 cells/mL with cellular composition of 3 % lipids, 40 % proteins, and 15 % carbohydrates-even though DOM accumulated and the dominant bacterial populations changed. There was a decrease in the maximum specific growth rate and flocculation efficiency from 0.72 d-1 to 0.45 d-1 and from 60 % to 48 %, respectively. This study shows the potential of repeated (at least five times) flocculation and reuse of media as a possible way of reducing the costs of water and nutrients with some tradeoffs in growth rate and flocculation efficiency.

Critical Hierarchical Appraisal and Reporting Tool for Composite Measures (CHAOS).

Background Composite measures are often used to represent certain concepts that cannot be measured with single variables and can be used as diagnoses, prognostic factors, or outcomes in clinical or health research. For example, frailty is a diagnosis confirmed based on the number of age-related symptoms and has been used to predict major health outcomes. However, undeclared assumptions and problems are prevalent among composite measures. Thus, we aim to propose a reporting guide and an appraisal tool for identifying these assumptions and problems. Methods We developed this reporting and assessment tool based on evidence and the consensus of experts pioneering research on index mining and syndrome mining. We designed a development framework for composite measures and then tested and revised it based on several composite measures commonly used in medical research, such as frailty, body mass index (BMI), mental illness diagnoses, and innovative indices mined for mortality prediction. We extracted review questions and reporting items from various issues identified by the development framework. This panel reviewed the identified issues, considered other aspects that might have been neglected in previous studies, and reached a consensus on the questions to be used by the reporting and assessment tool. Results We selected 19 questions in seven domains for reporting or critical assessment. Each domain contains review questions for authors and readers to critically evaluate the interpretability and validity of composite measures, which include candidate variable selection, variable inclusion and assumption declaration, data processing, weighting scheme, methods to aggregate information, composite measure interpretation and justification, and recommendations on the use. Conclusions For all seven domains, interpretability is central with respect to composite measures. Variable inclusion and assumptions are important clues to show the connection between composite measures and their theories. This tool can help researchers and readers understand the appropriateness of composite measures by exploring various issues. We recommend using this Critical Hierarchical Appraisal and repOrting tool for composite measureS (CHAOS) along with other critical appraisal tools to evaluate study design or risk of bias.

Combining Neuropsychological Assessment with Neuroimaging to Distinguish Early-Stage Alzheimer's Disease from Frontotemporal Lobar Degeneration in Non-Western Tonal Native Language-Speaking Individuals Living in Taiwan: A Case Series.

Neuropsychological tests (NPTs), which are routinely used in clinical practice for assessment of dementia, are also considered to be essential for differential diagnosis of Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD), especially the behavioral variants of frontotemporal dementia (bvFTD) and primary progressive aphasia (PPA) at their initial clinical presentations. However, the heterogeneous features of these diseases, which have many overlapping signs, make differentiation between AD and FTLD highly challenging. Moreover, NPTs were primarily developed in Western countries and for native speakers of non-tonal languages. Hence, there is an ongoing dispute over the validity and reliability of these tests in culturally different and typologically diverse language populations. The purpose of this case series was to examine which of the NPTs adjusted for Taiwanese society may be used to distinguish these two diseases. Since AD and FTLD have different effects on individuals' brain, we combined NPTs with neuroimaging. We found that participants diagnosed with FTLD had lower scores in NPTs assessing language or social cognition than AD participants. PPA participants also had lower measures in the Free and Cued Selective Reminding Test than those diagnosed with bvFTD, while bvFTD participants showed poorer performances in the behavioral measures than PPA participants. In addition, the initial diagnosis was supported by the standard one-year clinical follow-up.

Timing and Trends for Municipal Wastewater, Lab-Confirmed Case, and Syndromic Case Surveillance of COVID-19 in Raleigh, North Carolina.

Objectives. To compare 4 COVID-19 surveillance metrics in a major metropolitan area. Methods. We analyzed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater influent and primary solids in Raleigh, North Carolina, from April 10 through December 13, 2020. We compared wastewater results with lab-confirmed COVID-19 cases and syndromic COVID-like illness (CLI) cases to answer 3 questions: (1) Did they correlate? (2) What was the temporal alignment of the different surveillance systems? (3) Did periods of significant change (i.e., trends) align? Results. In the Raleigh sewershed, wastewater influent, wastewater primary solids, lab-confirmed cases, and CLI were strongly or moderately correlated. Trends in lab-confirmed cases and wastewater influent were observed earlier, followed by CLI and, lastly, wastewater primary solids. All 4 metrics showed sustained increases in COVID-19 in June, July, and November 2020 and sustained decreases in August and September 2020. Conclusions. In a major metropolitan area in 2020, the timing of and trends in municipal wastewater, lab-confirmed case, and syndromic case surveillance of COVID-19 were in general agreement. Public Health Implications. Our results provide evidence for investment in SARS-CoV-2 wastewater and CLI surveillance to complement information provided through lab-confirmed cases. (Am J Public Health. 2023;113(1):79-88. https://doi.org/10.2105/AJPH.2022.307108).