Demographic vital rates and population growth: rethinking the relationship in a harvested elk population

Understanding the nature of the relationship between demographic vital rates and the rate of population change (λ) is important for determining effective strategies for population management and conservation. We examined the relative impacts of various demographic vital rates on λ within the range of temporal vital rate variability observed in a harvested population to test the hypotheses that adult survival rates in ungulates are relatively invariant when compared to other vital rates and that variability in calf survival has a greater influence on rates of population change than adult survival. Vital rates were estimated for an elk (_Cervus elaphus_) population at Fort Riley, Kansas from October 2003 – February 2007. The magnitude of adult survival rates were similar to other harvested populations and models including a negative relationship between survival and age received the highest levels of support. Prime-age adult survival had the highest stage-specific elasticity values, indicating a high contribution of these matrix elements to λ. Life-stage simulation analysis indicated that variation in calf survival had the highest correlation with variation in λ (r^2^ = 0.61). Our results suggest that adult survival rates in harvested populations may experience increased levels of variability, but that calf survival rates have the greatest relative influence on λ due to the wider range of variability observed for this vital rate

Semiparametric Relative-risk Regression for Infectious Disease Data

This paper introduces semiparametric relative-risk regression models for infectious disease data based on contact intervals, where the contact interval from person i to person j is the time between the onset of infectiousness in i and infectious contact from i to j. The hazard of infectious contact from i to j is \lambda_0(\tau)r(\beta_0^T X_{ij}), where \lambda_0(\tau) is an unspecified baseline hazard function, r is a relative risk function, \beta_0 is an unknown covariate vector, and X_{ij} is a covariate vector. When who-infects-whom is observed, the Cox partial likelihood is a profile likelihood for \beta maximized over all possible \lambda_0(\tau). When who-infects-whom is not observed, we use an EM algorithm to maximize the profile likelihood for \beta integrated over all possible combinations of who-infected-whom. This extends the most important class of regression models in survival analysis to infectious disease epidemiology.Comment: 38 pages, 5 figure

A 24-month updated analysis of the comparative effectiveness of ZUMA-5 (axi-cel) vs. SCHOLAR-5 external control in relapsed/refractory follicular lymphoma

Follicular lymphoma; Axicabtagene ciloleucel; Comparative effectivenessLimfoma fol·licular; Axicabtagene ciloleucel; Eficàcia comparativaLinfoma folicular; Axicabtagene ciloleucel; Eficacia comparativaBackground In the ZUMA-5 trial (Clinical trials identification: NCT03105336), axicabtagene ciloleucel (axi-cel; a chimeric antigen receptor T-cell therapy) demonstrated high rates of durable response in relapsed/refractory (r/r) follicular lymphoma (FL) patients and clear superiority relative to the SCHOLAR-5 external control cohort. We update this comparison using the ZUMA-5 24-month data. Research design and methods The SCHOLAR-5 cohort is comprised of r/r FL patients who initiated ≥3rd line of therapy after July 2014 and meeting ZUMA-5 eligibility criteria. Groups were balanced for patient characteristics through propensity scoring on prespecified prognostic factors using standardized mortality ratio (SMR) weighting. The overall response rate was compared using a weighted logistic regression. Time-to-event outcomes were evaluated using a Cox regression. Results For SCHOLAR-5, the sum of weights for the 143 patients was 85 after SMR weighting, versus 86 patients in ZUMA-5. The median follow-up was 29.4 months and 25.4 months for ZUMA-5 and SCHOLAR-5, respectively. The hazard ratios for overall survival and progression-free survival were 0.52 (95% confidence interval (CI): 0.28–0.95) and 0.28 (95% CI: 0.17–0.45), favoring axi-cel. Conclusion This updated analysis, using a longer minimum follow-up than a previously published analysis, shows that the improved efficacy of axi-cel, relative to available therapies, in r/r FL is durable.This manuscript was funded by Kite, a Gilead Company

Expression of the platelet-activating factor receptor enhances benzyl isothiocyanate-induced apoptosis in murine and human melanoma cells

Melanoma cells often express platelet‑activating factor receptor (PAF‑R), which has been demonstrated to increase metastatic behavior. However, the effect of PAF‑R on the responsiveness of melanoma to naturally occurring cytotoxic agents remains to be elucidated. The present study aimed to determine the relative cytotoxicity and mechanism of benzyl isothiocyanate (BITC), a component of cruciferous vegetables, in melanoma cells expressing PAF‑R. To evaluate the importance of PAF‑R signaling in melanoma cell growth, PAF‑R‑negative murine B16F10 cells were transduced with a retrovirus containing the cDNA for PAF‑R to generate cells stably expressing PAF‑R (B16‑PAF‑R) or an empty vector (MSCV) to generate PAF‑R‑deficient B16‑MSCV control cells. Activation of PAF‑R, using the PAF‑R agonist, 1‑hexadecyl‑2‑N‑methylcarbamoyl‑3‑glycerophosphocholine, induced an increase in the proliferation of B16‑PAF‑R cells compared with the B16‑MSCV cells. Reverse transcription quantitative polymerase chain reaction revealed the presence of functional PAF‑R in human melanoma SK23MEL cells, but not in SK5MEL cells. The present study investigated the effect of BITC treatments on the survival of murine and human melanoma cells, in the presence or absence of functional PAF‑R. The results revealed that treatment with BITC decreased the survival rate of the PAF‑R‑positive and negative murine and human melanoma cells. However, the expression of PAF‑R substantially augmented BITC‑mediated cytotoxicity in the PAF‑R‑positive cells at lower concentrations compared with the PAF‑R‑negative cells. In order to determine the underlying mechanism, flow cytometric analysis was used, which demonstrated a significant increase in the generation of reactive oxygen species (ROS) in the B16‑PAF‑R cells compared with the B16‑MSCV cells, which enhanced apoptosis by BITC, as measured by increased caspase‑3/7 luminescence. Notably, the BITC‑mediated decreased cell survival rate, increased ROS and increased apoptosis in the B16‑PAF‑R cells were significantly attenuated by the antioxidant, vitamin C, indicating ROS involvement. Additionally, the WEB2086 PAF‑R antagonist, inhibited the BITC‑mediated enhancement of apoptosis in the B16‑PAF‑R cells, indicating a role for PAF‑R‑signaling in the BITC‑mediated effects. These findings indicated that the selectivity of BITC towards PAF‑R in melanoma offers a promising chemopreventive agent for PAF‑R‑positive melanoma treatment

The role of adrenomedullin as a growth regulatory peptide in the normal and malignant setting

Adrenomedullin (AM ) is a recently discovered pluripo1ent peptide initially isolated fraro a human adrenal gland tumor (pheochromocytoma). Adrenomedullin has been shown to have an ancient origin with immunoreactive species fOWld in maromals, birds, reptiles, amphibians, fish , and eemnoderms (s t a r fish ). Given its highly conserved evolutionary expression, AM is thought te playa critica! !•ole in spedes survival. This peptide has been show lo mediate a variety of physiological fu netlons, of which iis involvement in growth r egulation wil1 be tbe central focus of this papero In the following text, we will review the cited Iiterature in this area and inelude our own observations regarding AM express10n in carcinogenesis, embryogenesis, and wound r epair. Adrenomedullin will be shown to induce both growth promotian or growth suppression depending on the taTget cell examined aud the sUITounding nutritional environment in which the analysis was done. Its implied role as a mitogen, aogiogenic fador, and apoplosis survival factor will be critiqued and evaluated relative to its impor tance in the cel! proHferation process. Finally, we will review the a ntimicrobiaJ effect AM has on severa1 human pathogens ( Es•cherichia coli and Candidn albi.cans) and demonstrate its partieipation in the host immune response syslem as a first line defense peptide

Glioblastoma: Vascular Habitats Detected at Preoperative Dynamic Susceptibility-weighted Contrast-enhanced Perfusion MR Imaging Predict Survival

[EN] Purpose: To determine if preoperative vascular heterogeneity of glioblastoma is predictive of overall survival of patients undergoing standard-of-care treatment by using an unsupervised multiparametric perfusion-based habitat-discovery algorithm. Materials and Methods: Preoperative magnetic resonance (MR) imaging including dynamic susceptibility-weighted contrast material-enhanced perfusion studies in 50 consecutive patients with glioblastoma were retrieved. Perfusion parameters of glioblastoma were analyzed and used to automatically draw four reproducible habitats that describe the tumor vascular heterogeneity: high-angiogenic and low-angiogenic regions of the enhancing tumor, potentially tumor-infiltrated peripheral edema, and vasogenic edema. Kaplan-Meier and Cox proportional hazard analyses were conducted to assess the prognostic potential of the hemodynamic tissue signature to predict patient survival. Results: Cox regression analysis yielded a significant correlation between patients' survival and maximum relative cerebral blood volume (rCBV(max)) and maximum relative cerebral blood flow (rCBF(max)) in high-angiogenic and low-angiogenic habitats (P < .01, false discovery rate-corrected P < .05). Moreover, rCBF(max) in the potentially tumor-infiltrated peripheral edema habitat was also significantly correlated (P < .05, false discovery rate-corrected P < .05). Kaplan-Meier analysis demonstrated significant differences between the observed survival of populations divided according to the median of the rCBV(max) or rCBF(max) at the high-angiogenic and low-angiogenic habitats (log-rank test P < .05, false discovery rate-corrected P < .05), with an average survival increase of 230 days. Conclusion: Preoperative perfusion heterogeneity contains relevant information about overall survival in patients who undergo standard-of-care treatment. The hemodynamic tissue signature method automatically describes this heterogeneity, providing a set of vascular habitats with high prognostic capabilities.Study supported by H2020 European Institute of Innovation and Technology (POC-2016.SPAIN-07) and Universitat Politecnica de Valencia (PAID-10-14). J.J.A., E.F.G., and J.M.G.G. supported by Secretaria de Estado de Investigacion, Desarrollo e Innovacion (DPI2016-80054-R, TIN2013-43457-R). E.F.G. supported by CaixaImpulse program from Fundacio Bancaria "la Caixa" (LCF/TR/CI16/10010016). E.F.G and A.A.B. supported by the Universitat Politecnica de Valencia Instituto Investigacion Sanitaria de La Fe (C05).Juan -Albarracín, J.; Fuster García, E.; Pérez-Girbés, A.; Aparici-Robles, F.; Alberich Bayarri, A.; Revert Ventura, AJ.; Martí Bonmatí, L.... (2018). Glioblastoma: Vascular Habitats Detected at Preoperative Dynamic Susceptibility-weighted Contrast-enhanced Perfusion MR Imaging Predict Survival. Radiology. 287(3):944-954. https://doi.org/10.1148/radiol.2017170845S944954287

Estimate risk difference and number needed to treat in survival analysis

The hazard ratio (HR) is a measure of instantaneous relative risk of an increase in one unit of the covariate of interest, which is widely reported in clinical researches involving time-to-event data. However, the measure fails to capture absolute risk reduction. Other measures such as number needed to treat (NNT) and risk difference (RD) provide another perspective on the effectiveness of an intervention, and can facilitate clinical decision making. The article aims to provide a step-by-step tutorial on how to compute RD and NNT in survival analysis with R. For simplicity, only one measure (RD or NNT) needs to be illustrated, because the other measure is a reverse of the illustrated one (NNT=1/RD). An artificial dataset is composed by using the survsim package. RD and NNT are estimated with Austin method after fitting a Cox-proportional hazard regression model. The confidence intervals can be estimated using bootstrap method. Alternatively, if the standard errors (SEs) of the survival probabilities of the treated and control group are given, confidence intervals can be estimated using algebraic calculations. The pseudo-value model provides another method to estimate RD and NNT. Details of R code and its output are shown and explained in the main text