Improving Cancer Probability Estimation in Nondiagnostic Bronchoscopies: A Meta-analysis.

BACKGROUND: In patients with peripheral pulmonary lesions (PPLs), nondiagnostic bronchoscopy results are not uncommon. The conventional approach to estimate the probability of cancer (pCA) after bronchoscopies relies on dichotomous test assumptions, using prevalence, sensitivity, and specificity to determine negative predictive value. However, bronchoscopy is a multidisease test, raising concerns about the accuracy of dichotomous methods. RESEARCH QUESTION: By how much does calculating pCA using a dichotomous approach (pCAdichotomous) underestimate the true pCA when applied to multidisease tests like bronchoscopy for the diagnosis of PPL? METHODS: In this meta-analysis of cohort studies involving radial endobronchial ultrasound for PPL, Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines were followed, constructing 2 × 2 contingency tables for calculating pCAdichotomous. For the multidisease test approach, 3 × 3 contingency tables for calculating probability of malignancy for a test that can have multiple test different categories of results and can diagnose multiple diseases (pCAmultidisease) using the likelihood ratio (LR) method for nondiagnostic results (LR(T0)) was used. Observed malignancy rates in patients with nondiagnostic results were compared with pCAdichotomous and pCAmultidisease. RESULTS: In 46 studies (7,506 patients), malignancy was the underlying diagnosis in 76%, another specific disease in 13%, and nonspecific fibrosis or scar in 10%. The percentage of patients with nondiagnostic results who had malignancy matched pCAmultidisease across all studies. In contrast, pCAdichotomous consistently underestimated cancer risk (median difference, 0.12; interquartile range, 0.06-0.23), particularly in studies with a higher prevalence of nonmalignant disease. The pooled LR(T0) was 0.46 (95% CI, 0.40-0.52; I2 = 76%; P < .001) and correlated with the prevalence of nonmalignant diseases (P = .001). INTERPRETATION: Conventional dichotomous methods for estimating pCA after nondiagnostic bronchoscopies underestimate the likelihood of malignancy. Physicians should opt for the multidisease test approach when interpreting bronchoscopy results.

Predicting Optimal Antimalarial Drug Combinations from a Standardized Plasmodium falciparum Humanized Mouse Model.

The development of new combinations of antimalarial drugs is urgently needed to prevent the spread of parasites resistant to drugs in clinical use and contribute to the control and eradication of malaria. In this work, we evaluated a standardized humanized mouse model of erythrocyte asexual stages of Plasmodium falciparum (PfalcHuMouse) for the selection of optimal drug combinations. First, we showed that the replication of P. falciparum was robust and highly reproducible in the PfalcHuMouse model by retrospective analysis of historical data. Second, we compared the relative value of parasite clearance from blood, parasite regrowth after suboptimal treatment (recrudescence), and cure as variables of therapeutic response to measure the contributions of partner drugs to combinations in vivo. To address the comparison, we first formalized and validated the day of recrudescence (DoR) as a new variable and found that there was a log-linear relationship with the number of viable parasites per mouse. Then, using historical data on monotherapy and two small cohorts of PfalcHuMice evaluated with ferroquine plus artefenomel or piperaquine plus artefenomel, we found that only measurements of parasite killing (i.e., cure of mice) as a function of drug exposure in blood allowed direct estimation of the individual drug contribution to efficacy by using multivariate statistical modeling and intuitive graphic displays. Overall, the analysis of parasite killing in the PfalcHuMouse model is a unique and robust experimental in vivo tool to inform the selection of optimal combinations by pharmacometric pharmacokinetic and pharmacodynamic (PK/PD) modeling.

Breast and Lung Effusion Survival Score Models: Improving Survival Prediction in Patients With Malignant Pleural Effusion and Metastasis.

BACKGROUND: Evidence-based guidelines recommend management strategies for malignant pleural effusions (MPEs) based on life expectancy. Existent risk-prediction rules do not provide precise individualized survival estimates. RESEARCH QUESTION: Can a newly developed continuous risk-prediction survival model for patients with MPE and known metastatic disease provide precise survival estimates? STUDY DESIGN AND METHODS: Single-center retrospective cohort study of patients with proven malignancy, pleural effusion, and known metastatic disease undergoing thoracentesis from 2014 through 2017. The outcome was time from thoracentesis to death. Risk factors were identified using Cox proportional hazards models. Effect-measure modification (EMM) was tested using the Mantel-Cox test and was addressed by using disease-specific models (DSMs) or interaction terms. Three DSMs and a combined model using interactions were generated. Discrimination was evaluated using Harrell's C-statistic. Calibration was assessed by observed-minus-predicted probability graphs at specific time points. Models were validated using patients treated from 2010 through 2013. Using LENT (pleural fluid lactate dehydrogenase, Eastern Cooperative Oncology Group performance score, neutrophil-to-lymphocyte ratio and tumor type) variables, we generated both discrete (LENT-D) and continuous (LENT-C) models, assessing discrete vs continuous predictors' performances. RESULTS: The development and validation cohort included 562 and 727 patients, respectively. The Mantel-Cox test demonstrated interactions between cancer type and neutrophil to lymphocyte ratio (P < .0001), pleural fluid lactate dehydrogenase (P = .029), and bilateral effusion (P = .002). DSMs for lung, breast, and hematologic malignancies showed C-statistics of 0.72, 0.72, and 0.62, respectively; the combined model's C-statistics was 0.67. LENT-D (C-statistic, 0.60) and LENT-C (C-statistic, 0.65) models underperformed. INTERPRETATION: EMM is present between cancer type and other predictors; thus, DSMs outperformed the models that failed to account for this. Discrete risk-prediction models lacked enough precision to be useful for individual-level predictions.

Chemical Composition and Biological Activities of Artemisia pedemontana subsp. assoana Essential Oils and Hydrolate.

Given the importance of the genus Artemisia as a source of valuable natural products, the rare plant Artemisia pedemontana subspecies assoana, endemic to the Iberian Peninsula, has been experimentally cultivated in the greenhouse and aeroponically, to produce biomass for essential oil (EO) extraction. The chemical composition of the EOs was analyzed, and their plant protection (insects: Spodoptera littoralis, Rhopalosiphum padi, and Myzus persicae; plants: Lactuca sativa and Lolium perenne; fungi: Aspergillus niger; and nematode: Meloidogyne javanica) and antiparasitic (Trypanosoma cruzi, Phytomonas davidi, and antiplasmodial by the ferriprotoporphyrin biocrystallization inhibition test) properties were studied, in addition to the hydrolate by-product. The EOs showed a 1,8-cineole and camphor profile, with quantitative and qualitative chemical differences between the cultivation methods. These oils had moderate insect antifeedant, antifungal, and phytotoxic effects; were trypanocidel; and exhibited moderate phytomonacidal effects, while the hydrolate showed a strong nematicidal activity. Both EOs were similarly antifeedant; the EO from the greenhouse plants (flowering stage) was more biocidal (antifungal, nematicidal, and phytotoxic) than the EO from the aeroponic plants (growing stage), which was more antiparasitic. The major components of the oils (1,8-cineole and camphor), or their 1:1 combination, did not explain any of these effects. We can conclude that these EOs have potential applications as insect antifeedants, and as antifungal or antiparasitic agents, depending on the cultivation method, and that the hydrolate byproduct is a potent nematicidal.

Antiparasitic Activity of Diterpenoids Against Trypanosoma cruzi.

Twenty-seven diterpenes, including abietanes, labdanes, abeoabietanes, halimanes, and pimaranes, have been evaluated against epimastigote and intracellular amastigote forms of Trypanosoma cruzi and also against LC5 and NCTC cell lines. Royleanones (3, 4, and 5) and a further abietane (12), obtained by purification of Plectranthus spp. extracts, were the most active compounds on epimastigotes, showing IC50 values similar (1.73 µg/mL, 12) or even lower (0.39, 0.99, and 1.20 µg/mL, 3, 4, and 5 respectively) than the positive control nifurtimox (2.3 µg/mL). On intracellular amastigotes, abietanes 3, 4, and 5 showed a significant activity with IC50 values of 0.83, < 0.31, and 0.62 µg/mL, respectively, but were less potent than the positive control nifurtimox (IC50 < 0.16 µg/mL). Compounds 3, 4, and 5 were not cytotoxic to LC5 and NCTC 929 cells at 1 µg/mL.

Trypanocidal Effects of Essential Oils from Selected Medicinal Plants. Synergy among the Main Components.

Fourteen essential oils (EOs) from selected live germplasm of medicinal plants have been tested for their antitrypanosomal and cytotoxic activity. These plants have been domesticated and maintained under experimental cultivation. Their EOs were tested on epimastigote forms of Trypanosoma cruzi strain Y and human lung fibroblasts LC5 cell line, along with the major components of the active oils, both separately and in binary combinations. Mentha rotundifolia, Thymus zygis, T. vulgaris and Hyssopus officinalis were the most active EOs against T. cruzi. Among the main components of these EOs (1-8-cineole, thymol, p-cymene, piperitenone oxide, ß-pinene, γ-terpinene, carvacrol and linalool), the most active against the parasite and less toxic to human cells was thymol. In general, the activity of the main components did not exceed that of their origin EO, and the study of the activity of these compounds in combination indicates the existence of antagonistic and synergistic effects depending on the concentration tested.