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Conclusions This case highlights the difficulty of distinction between infection and inflammation in patients with joint swelling and pain, especially in the age of disease-modifying drugs (DMARDs) and the concomitant risk of atypical infections. A review of the literature identified eight additional published cases, which suggests that Mycobacterium marinum infection is a rare but recognized complication of DMARD therapy. It can mimic a flare of the underlying arthritis potentially leading to diagnostic delays, and requires differential diagnostic methods to identify the pathogen and pave the way for appropriate treatment. © The Author(s) 2020.Background Statins have anticancer properties by acting as competitive inhibitors of the mevalonate pathway. They also have anti-inflammatory activity, but their role in suppressing inflammation in a cancer context has not been investigated to date. Methods We have analyzed the relationship between statin use and tumor-associated macrophages (TAMs) in a cohort of 262 surgically resected primary human lung adenocarcinomas. TAMs were evaluated by multiplex immunostaining for the CD68 pan-TAM marker and the CD163 protumorigenic TAM marker followed by digital slide scanning and partially automated quantitation. Links between statin use and tumor stage, virulence, and cancer-specific survival were also investigated in a wider cohort of 958 lung adenocarcinoma cases. All statistical tests were two-sided. Results We found a statin dose-dependent reduction in protumorigenic TAMs (CD68+CD163+) in both stromal (P = .021) and parenchymal (P = .003) compartments within regions of in situ tumor growth, but this association was lost in invasive regions. No statistically significant relationship between statin use and tumor stage was observed, but there was a statin dose-dependent shift towards lower histological grade as assessed by growth pattern (P = .028). However, statin use was a predictor of slightly worse cancer-specific survival (P = .032), even after accounting for prognostic variables in a multivariable Cox proportional hazards survival model (hazard ratio = 1.38, 95% confidence interval = 1.04 to 1.84). Conclusions Statin use is associated with reduced numbers of protumorigenic TAMs within preinvasive lung adenocarcinoma and is related to reduced tumor invasiveness, suggesting a chemo-preventive effect in early tumor development. However, invasive disease is resistant to these effects, and no beneficial relationship between statin use and patient outcome is observed. © The Author(s) 2019. see more Published by Oxford University Press.We evaluated for the first time, to our knowledge, adverse health outcomes (AHOs) among US testicular cancer survivors (TCS) given chemotherapy (n = 381) vs surgery-only patients (n = 98) managed at a single institution, accounting for non-treatment-related risk factors to delineate chemotherapy's impact. Chemotherapy consisted largely of bleomycin-etoposide-cisplatin (BEP) administered in three or four cycles (BEPx3, n = 235; BEPx4, n = 82). Incidence of at least 3 AHOs was lowest in surgery-only TCS and increased with BEPx3, BEPx4, and other cisplatin-based regimens (12.2%, 40.8%, 52.5%, 54.8%; P less then .0001). Multivariable modeling assessed associations of risk factors and treatment with hearing impairment, tinnitus, peripheral neuropathy, and Raynaud phenomenon. Risk for each AHO statistically increased with both increasing chemotherapy burden (P less then .0001) and selected modifiable risk factors (P less then .05) hypertension (odds ratio [OR] = 2.40) and noise exposure (OR ≥ 2.3) for hearing impairment; noise exposure for tinnitus (OR ≥ 1.69); peripheral vascular disease for neuropathy (OR = 8.72); and current smoking for Raynaud phenomenon (OR = 2.41). Clinicians should manage modifiable risk factors for AHOs among TCS. © The Author(s) 2019. Published by Oxford University Press.Secondary data analysis, or the analysis of preexisting data, provides a powerful tool for the resourceful psychological scientist. Never has this been more true than now, when technological advances enable both sharing data across labs and continents and mining large sources of preexisting data. However, secondary data analysis is easily overlooked as a key domain for developing new open-science practices or improving analytic methods for robust data analysis. In this article, we provide researchers with the knowledge necessary to incorporate secondary data analysis into their methodological toolbox. We explain that secondary data analysis can be used for either exploratory or confirmatory work, and can be either correlational or experimental, and we highlight the advantages and disadvantages of this type of research. We describe how transparency-enhancing practices can improve and alter interpretations of results from secondary data analysis and discuss approaches that can be used to improve the robustness of reported results. We close by suggesting ways in which scientific subfields and institutions could address and improve the use of secondary data analysis.An individualized approach to identify acutely ill medical patients at increased risk of venous thromboembolism (VTE) and a low risk of bleeding to optimize the benefit and risk of extended thromboprophylaxis (ET) is needed. The International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) VTE risk score has undergone extensive external validation in medically ill patients for in-hospital use and a modified model was used in the MARINER trial of ET also incorporating an elevated D-dimer. The MAGELLAN study demonstrated efficacy with rivaroxaban but had excess bleeding. This retrospective analysis investigated whether the modified IMPROVE VTE model with an elevated D-dimer could identify a high VTE risk subgroup of patients for ET from a subpopulation of the MAGELLAN study, which was previously identified as having a lower risk of bleeding. We incorporated the modified IMPROVE VTE score using a cutoff score of 4 or more or 2 and 3 with an elevated D-dimer (>2 times the upper limit of normal) to the MAGELLAN subpopulation.
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