Responsiveness of Candidate Genes on CoPv01CDRK/PhgPv01CDRK Loci in Common Bean Challenged by Anthracnose and Angular Leaf Spot Pathogens.

Anthracnose (ANT) and angular leaf spot (ALS) are significant diseases in common bean, leading to considerable yield losses under specific environmental conditions. The California Dark Red Kidney (CDRK) bean cultivar is known for its resistance to multiple races of both pathogens. Previous studies have identified the CoPv01CDRK/PhgPv01CDRK resistance loci on chromosome Pv01. Here, we evaluated the expression levels of ten candidate genes near the CoPv01CDRK/PhgPv01CDRK loci and plant defense genes using quantitative real-time PCR in CDRK cultivar inoculated with races 73 of Colletotrichum lindemuthianum and 63-39 of Pseudocercospora griseola. Gene expression analysis revealed that the Phvul.001G246300 gene exhibited the most elevated levels, showing remarkable 7.8-fold and 8.5-fold increases for ANT and ALS, respectively. The Phvul.001G246300 gene encodes an abscisic acid (ABA) receptor with pyrabactin resistance, PYR1-like (PYL) protein, which plays a central role in the crosstalk between ABA and jasmonic acid responses. Interestingly, our results also showed that the other defense genes were initially activated. These findings provide critical insights into the molecular mechanisms underlying plant defense against these diseases and could contribute to the development of more effective disease management strategies in the future.

Exploring in vitro solubility of lamotrigine in physiologically mimetic conditions to prospect the in vivo dissolution in pediatric population.

Pediatric drugs knowledge still leaves several gaps to be filled, all the while many biopharmaceutic properties applied to adults do not work in pediatrics. The solubility in many cases is extrapolated to pediatrics; however, sometimes it may not represent the real scenario. In this context, the aim of this study was to assess the possibility of the extrapolation of the solubility data assumed for adults to children aged 2-12 years using lamotrigine (LTG) as a model. LTG showed that its solubility is dependent on the pH of the medium, no precipitate formation was seen, and biomimetic media showed a greater capacity to solubilize it. Based on the dose number (D0 ) in adults, the LTG was soluble in acidic pH media and poorly soluble in neutral to basic. Similar behavior was found in conditions which mimic children aged 10-12 years at a dose of 5 and 15 mg/kg. The D0 for 5-year-old children at a dose of 15 mg/kg showed different behaviors between biorelevant and pharmacopeial buffers media. For children aged 2-3 years, LTG appeared to be poorly soluble under both gastric and intestinal conditions. Solubility was dependent on the volume of fluid calculated for each age group, and this may impact the development of better pharmaceutical formulations for this population, better pharmacokinetic predictions in tools as PBPK, and physiologically-based biopharmaceutics modeling, greater accuracy in the justifications for biowaiver, and many other possibilities.

The unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications.

In this paper, we propose and derive a new regression model for response variables defined on the open unit interval. By reparameterizing the unit generalized half-normal distribution, we get the interpretation of its location parameter as being a quantile of the distribution. In addition, we can evaluate effects of the explanatory variables in the conditional quantiles of the response variable as an alternative to the Kumaraswamy quantile regression model. The suitability of our proposal is demonstrated with two simulated examples and two real applications. For such data sets, the obtained fits of the proposed regression model are compared with that provided by a Kumaraswamy regression model.

Routine laboratory biomarkers used to predict Gram-positive or Gram-negative bacteria involved in bloodstream infections.

This study evaluated routine laboratory biomarkers (RLB) to predict the infectious bacterial group, Gram-positive (GP) or Gram-negative (GN) associated with bloodstream infection (BSI) before the result of blood culture (BC). A total of 13,574 BC of 6787 patients (217 BSI-GP and 238 BSI-GN) and 68 different RLB from these were analyzed. The logistic regression model was built considering BSI-GP or BSI-GN as response variable and RLB as covariates. After four filters applied total of 320 patients and 16 RLB remained in the Complete-Model-CM, and 4 RLB in the Reduced-Model-RM (RLB p > 0.05 excluded). In the RM, only platelets, creatinine, mean corpuscular hemoglobin and erythrocytes were used. The reproductivity of both models were applied to a test bank of 2019. The new model presented values to predict BSI-GN of the area under the curve (AUC) of 0.72 and 0.69 for CM and RM, respectively; with sensitivity of 0.62 and 0.61 (CM and RM) and specificity of 0.67 for both. These data confirm the discriminatory capacity of the new models for BSI-GN (p = 0.64). AUC of 0.69 using only 4 RLB, associated with the patient's clinical data could be useful for better targeted antimicrobial therapy in BSI.

An overview on parametric quantile regression models and their computational implementation with applications to biomedical problems including COVID-19 data.

Quantile regression allows us to estimate the relationship between covariates and any quantile of the response variable rather than the mean. Recently, several statistical distributions have been considered for quantile modeling. The objective of this study is to provide a new computational package, two biomedical applications, one of them with COVID-19 data, and an up-to-date overview of parametric quantile regression. A fully parametric quantile regression is formulated by first parameterizing the baseline distribution in terms of a quantile. Then, we introduce a regression-based functional form through a link function. The density, distribution, and quantile functions, as well as the main properties of each distribution, are presented. We consider 18 distributions related to normal and non-normal settings for quantile modeling of continuous responses on the unit interval, four distributions for continuous response, and one distribution for discrete response. We implement an R package that includes estimation and model checking, density, distribution, and quantile functions, as well as random number generators, for distributions using quantile regression in both location and shape parameters. In summary, a number of studies have recently appeared applying parametric quantile regression as an alternative to the distribution-free quantile regression proposed in the literature. We have reviewed a wide body of parametric quantile regression models, developed an R package which allows us, in a simple way, to fit a variety of distributions, and applied these models to two examples with biomedical real-world data from Brazil and COVID-19 data from US for illustrative purposes. Parametric and non-parametric quantile regressions are compared with these two data sets.

Pharmacodynamic evaluation of suppression of in vitro resistance in Acinetobacter baumannii strains using polymyxin B-based combination therapy.

The emergence of polymyxin resistance in Gram-negative bacteria infections has motivated the use of combination therapy. This study determined the mutant selection window (MSW) of polymyxin B alone and in combination with meropenem and fosfomycin against A. baumannii strains belonging to clonal lineages I and III. To evaluate the inhibition of in vitro drug resistance, we investigate the MSW-derived pharmacodynamic indices associated with resistance to polymyxin B administrated regimens as monotherapy and combination therapy, such as the percentage of each dosage interval that free plasma concentration was within the MSW (%TMSW) and the percentage of each dosage interval that free plasma concentration exceeded the mutant prevention concentration (%T>MPC). The MSW of polymyxin B varied between 1 and 16 µg/mL for polymyxin B-susceptible strains. The triple combination of polymyxin B with meropenem and fosfomycin inhibited the polymyxin B-resistant subpopulation in meropenem-resistant isolates and polymyxin B plus meropenem as a double combination sufficiently inhibited meropenem-intermediate, and susceptible strains. T>MPC 90% was reached for polymyxin B in these combinations, while %TMSW was 0 against all strains. TMSW for meropenem and fosfomycin were also reduced. Effective antimicrobial combinations significantly reduced MSW. The MSW-derived pharmacodynamic indices can be used for the selection of effective combination regimen to combat the polymyxin B-resistant strain.

A collection of parametric modal regression models for bounded data.

Modal regression is an alternative approach for investigating the relationship between the most likely response and covariates and can hence reveal important structure missed by usual regression methods. This paper provides a collection of parametric mode regression models for bounded response variable by considering some recently introduced probability distributions with bounded support along with the well-established Beta and Kumaraswamy distribution. The main properties of the distributions are highlighted and compared. An empirical comparison between the considered modal regression is demonstrated through the analysis of three data sets from health and social science. For reproducible research, the proposed models are freely available to users as an R package unitModalReg.

A parametric quantile regression approach for modelling zero-or-one inflated double bounded data.

Over the last decades, the challenges in applied regression have been changing considerably, and full probabilistic modeling rather than predicting just means is crucial in many applications. Motivated by two applications where the response variable is observed on the unit-interval and inflated at zero or one, we propose a parametric quantile regression considering the unit-Weibull distribution. In particular, we are interested in quantifying the influence of covariates on the quantiles of the response variable. The maximum likelihood method is used for parameters estimation. Monte Carlo simulations reveal that the maximum likelihood estimators are nearly unbiased and consistent. Also, we define a residual analysis to assess the goodness of fit.

Pharmacokinetics of amoxicillin in obese and nonobese subjects.

AIMS: To compare the pharmacokinetics of amoxicillin (AMX) in obese and nonobese subjects, given as single dose 875-mg tablets. METHODS: A prospective, single-centre, open-label, clinical study was carried out involving 10 nonobese and 20 obese subjects given a dose of an AMX 875-mg tablet. Serial blood samples were collected between 0 and 8 hours after administration of AMX and plasma levels were quantified by liquid chromatography-tandem mass spectrometry. The pharmacokinetic parameters (PK) were calculated by noncompartmental analysis and means of the 2 groups were compared using Student t-test. Analysis of correlation between covariates and PK was performed using Pearson's correlation coefficient. RESULTS: Ten nonobese subjects (mean age 30.6 ± 7.12 y; body mass index 21.56 ± 1.95 kg/m2 ) and 20 obese subjects (mean age 34.47 ± 7.03 y; body mass index 33.17 ± 2.38 kg/m2 ) participated in the study. Both maximum concentration (Cmax ; 12.12 ± 4.06 vs. 9.66 ± 2.93 mg/L) and area under the curve (AUC)0-inf (34.18 ± 12.94 mg.h/L vs. 26.88 ± 9.24 mg.h/L) were slightly higher in nonobese than in obese subjects, respectively, but differences were not significant. The volume of distribution (V/F) parameter was statistically significantly higher in obese compared to nonobese patients (44.20 ± 17.85 L vs. 27.57 ± 12.96 L). Statistically significant correlations were observed for several weight metrics vs. AUC, Cmax , V/F and clearance, and for creatinine clearance vs. AUC, Cmax and clearance. CONCLUSION: In obese subjects, the main altered PK was V/F as a consequence of greater body weight. This may result in antibiotic treatment failure if standard therapeutic regimens are administered.

A discrete analog of Gumbel distribution: properties, parameter estimation and applications.

A discrete version of the Gumbel distribution (Type-I Extreme Value distribution) has been derived by using the general approach of discretization of a continuous distribution. Important distributional and reliability properties have been explored. It has been shown that depending on the choice of parameters the proposed distribution can be positively or negatively skewed; possess long-tail(s). Log-concavity of the distribution and consequent results have been established. Estimation of parameters by method of maximum likelihood, method of moments, and method of proportions has been discussed. A method of checking model adequacy and regression type estimation based on empirical survival function has also been examined. A simulation study has been carried out to compare and check the efficacy of the three methods of estimations. The distribution has been applied to model three real count data sets from diverse application area namely, survival times in number of days, maximum annual floods data from Brazil and goal differences in English premier league, and the results show the relevance of the proposed distribution.

Pharmacodynamic Effects of Sulbactam/Meropenem/Polymyxin-B Combination Against Extremely Drug Resistant Acinetobacter baumannii Using Checkerboard Information.

Aim: The aims of the study are to evaluate the activity of sulbactam, meropenem, and polymyxin B alone and in combination against six isolates of extremely drug resistant Acinetobacter baumannii and to determine dosing regimens that achieve a sufficient joint probability of target attainment (PTA) based on combination antimicrobial pharmacodynamics. Materials and Methods: The combinations were evaluated by the checkerboard method and were considered synergistic when the fractional inhibitory concentration index (FICI) ≤0.5. Pharmacodynamic analyses were carried out by evaluating dosing regimens that achieve ≥90% joint PTA at the percentage of time over a 24-h period wherein the free drug concentration is above the minimum inhibitory concentration (%fT> MIC) of 40% and 60% for meropenem and sulbactam, respectively, and 20 for the ratio of the area under the free drug concentration-time curve over MIC (fAUC/MIC) for polymyxin B. Results: For both polymyxin B-resistant and susceptible isolates, the addition of sulbactam in combination with meropenem and subinhibitory concentration of polymyxin B showed important synergistic activity (five isolates; FICI ≤0.281); the recommended dosing regimens were 2/4 g meropenem/sulbactam q8 hours and 0.5 mg/kg polymyxin B q12 hours. Conclusion: This in vitro study showed that sulbactam can significantly improve the action of meropenem and polymyxin B in OXA-producing A. baumannii isolates, especially when there are no new treatment options available for infections caused by these microorganisms.

Reduced bioavailability of oral amoxicillin tablets compared to suspensions in Roux-en-Y gastric bypass bariatric subjects.

AIMS: To evaluate the relative bioavailability of oral amoxicillin (AMX) tablets in comparison to AMX suspension in Roux-en-Y gastric bypass bariatric subjects. METHODS: A randomized, double-blind, cross-over study was performed on the bioavailability of oral AMX tablets and suspension in Roux-en-Y gastric bypass subjects operated at least 3 months previously . Doses of 875 mg of the AMX tablet or 800 mg of the AMX suspension were given to all the subjects, allowing a washout of 7 days between the periods. Blood samples were collected at 0, 0.25, 0.5, 1, 1.5, 2, 4, 6 and 8 hours after drug administration and the AMX levels were quantified by liquid chromatography coupled with triple quadrupole tandem mass spectrometry. The pharmacokinetic parameters were calculated by noncompartmental analysis, normalized to an 875 mg dose and the bioavailability of the AMX from the tablets was compared to that from the suspension formulation. RESULTS: Twenty subjects aged 42.65 ± 7.21 years and with a body mass index of 29.88 ± 4.36 kg/m2 were enrolled in the study. The maximum AMX plasma concentration of the tablets and the suspension (normalized to 875 mg) were 7.42 ± 2.99 mg/L and 8.73 ± 3.26 mg/L (90% confidence interval of 70.71-99.11), and the total area under the curve from time zero to infinity were 23.10 ± 7.41 mg.h/L and 27.59 ± 8.32 mg.h/L (90% confidence interval of 71.25-97.32), respectively. CONCLUSION: The tablets presented a lower bioavailability than the suspension formulation and the total absorbed amount of AMX in these subjects was lower in comparison to the standard AMX absorption rates in nonbariatric subjects, regardless of the formulation.

Pharmacodynamic Attainment of the Synergism of Meropenem and Fosfomycin Combination against Pseudomonas aeruginosa Producing Metallo-ß-Lactamase.

Fosfomycin combined with other antimicrobials has shown good efficacy against multidrug-resistant (MDR) bacteria in both in vitro and clinical studies; however, the activity of fosfomycin combined with other antimicrobials against metallo-ß-lactamase (MBL)-producing Pseudomonas aeruginosa strains has not been tested. The objective of this study was to determine the synergism and optimal intravenous dosing regimens of fosfomycin with meropenem against MDR and MBL-producing P. aeruginosa strains. The MICs of both antimicrobials were determined by the checkerboard method and analyzed by two synergism tests with 19 clones of P. aeruginosa isolates, 10 of which were MBL producers. A pharmacodynamic (PD) analysis was performed for meropenem (administered at 1 g every 8 h [q8h], 1.5 g every 6 h [q6h], and 2 g q8h) and fosfomycin (administered at 4 g q8h, 4 g q6h, 6 g q8h, and 8 g q8h) regimens with a dose reduction for renal impairment by determining the probability of target attainment (PTA) for target PD indices of meropenem (the percentage of the time in a 24-h duration at which the free drug concentration remains above the MIC [fT>MIC], ≥40%) and fosfomycin (the ratio of the area under the free drug concentration-versus-time curve over 24 h and the MIC [fAUC/MIC], ≥40.8). The combination reduced the MIC50 and MIC90 by 8-fold. Seven (44%) isolates with MICs in the intermediate or resistant ranges became sensitive to meropenem. For the MBL-producing isolates, the combination resulted in 40% of isolates becoming sensitive to meropenem. The meropenem regimens reached a PTA of ≥90% (MIC = 4 µg/ml) in 6 (32%) isolates when they were used as monotherapy and 13 (68%) isolates when they were combined with fosfomycin. None of the fosfomycin monotherapy regimens reached the PTA of ≥90% (MIC = 16 µg/ml). When combined with meropenem, the fosfomycin regimens reached the PTA of ≥90% in 14 (74%) isolates. The increase in pharmacodynamic activities resulting from the synergistic action of meropenem with fosfomycin demonstrates the potential relevance of this combination to fight infections caused by MDR and MBL-producing P. aeruginosa strains.

Mixture and nonmixture cure fraction models assuming discrete lifetimes: Application to a pelvic sarcoma dataset.

Different cure fraction models have been used in the analysis of lifetime data in presence of cured patients. This paper considers mixture and nonmixture models based on discrete Weibull distribution to model recurrent event data in presence of a cure fraction. The novelty of this study is the use of a discrete lifetime distribution in place of usual existing continuous lifetime distributions for lifetime data in presence of cured fraction, censored data, and covariates. In the verification of the fit of the proposed model it is proposed the use of randomized quantile residuals. An extensive simulation study is considered to evaluate the properties of the estimates of the parameters related to the proposed model. As an illustration of the proposed methodology, it is considered an application considering a medical dataset related to lifetimes in a retrospective cohort study conducted by Puchner et al. (2017) that consists of 147 consecutive cases with surgical treatment of a sarcoma of the pelvis between the years of 1980 and 2012.

Pharmacodynamic Evaluation of Fosfomycin against Escherichia coli and Klebsiella spp. from Urinary Tract Infections and the Influence of pH on Fosfomycin Activities.

Fosfomycin is widely used for the treatment of uncomplicated urinary tract infection (UTI), and it has recently been recommended that fosfomycin be used to treat infections caused by multidrug-resistant (MDR) Gram-negative bacilli. Whether urine acidification can improve bacterial susceptibility to fosfomycin oral dosing regimens has not been analyzed. The MIC of fosfomycin for 245 Gram-negative bacterial isolates, consisting of 158 Escherichia coli isolates and 87 Klebsiella isolates which were collected from patients with urinary tract infections, were determined at pH 6.0 and 7.0 using the agar dilution method. Monte Carlo simulation of the urinary fosfomycin area under the concentration-time curve (AUC) after a single oral dose of 3,000 mg fosfomycin and the MIC distribution were used to determine the probability of target attainment (PTA). Fosfomycin was effective against E. coli (MIC90 ≤ 16 µg/ml) but not against Klebsiella spp. (MIC90 > 512 µg/ml). Acidification of the environment increased the susceptibility of 71% of the bacterial isolates and resulted in a statistically significant decrease in bacterial survival. The use of a regimen consisting of a single oral dose of fosfomycin against an E. coli isolate with an MIC of ≤64 mg/liter was able to achieve a PTA of ≥90% for a target pharmacodynamic index (AUC/MIC) of 23 in urine; PTA was not achieved when the MIC was higher than 64 mg/liter. The cumulative fractions of the bacterial responses (CFR) were 99% and 55% against E. coli and Klebsiella spp., respectively, based on simulated drug exposure in urine with an acidic pH of 6.0. A decrease of the pH from 7.0 to 6.0 improved the PTA and CFR of the target pharmacodynamic index in both E. coli and Klebsiella isolates.

Pharmacodynamic Evaluation of the Potential Clinical Utility of Fosfomycin and Meropenem in Combination Therapy against KPC-2-Producing Klebsiella pneumoniae.

KPC-producing Klebsiella pneumoniae causes serious infections associated with high death rates worldwide. Combination therapy consisting of fosfomycin and a carbapenem is better than monotherapy to combat multidrug-resistant microorganisms, but no dosages for the combination have been defined. The MICs of meropenem and fosfomycin were evaluated against 18 clinical isolates of KPC-2-producing K. pneumoniae The activities of combination antimicrobials were also determined by the checkerboard method. The MIC50 and MIC90 of each agent alone and in combination were challenged against short (1.5-h) or prolonged (3-h) infusion regimens of meropenem (1 g every 8 h [q8h], 1.5 g q6h, 2 g q8h) and fosfomycin (4 g q8h, 6 g q6h, 8 g q8h) by Monte Carlo simulation to evaluate the time above the MIC of the free drug concentration as a percentage of the dosing interval (fT>MIC). The monotherapy MIC50s and MIC90s were 32 and 256 mg/liter for meropenem and 64 and 512 mg/liter for fosfomycin, respectively. Antimicrobial combination increased bacterial susceptibility to 1/4 the MIC50s and to 1/8 to 1/16 the MIC90s of monotherapy. The antimicrobial combination demonstrated a synergistic effect for at least two-thirds of the isolates. In combination therapy, fosfomycin regimens of 6 g q6h and 8 g q8h as a 3-h infusion against the MIC50 and MIC90 had better chances of achieving ≥90% probability of target attainment (PTA) of 70% fT>MIC. Meropenem regimens of 1.5 g q6h and 2 g q8h in prolonged infusion can achieve close to 90% PTA of 40% fT>MIC for MIC50 but not MIC90 The significant reduction in the MIC values and the achievement of appropriate PTA demonstrated that regimens containing fosfomycin with meropenem can be effective against KPC-2-producing K. pneumoniae.

Strategies for the treatment of polymyxin B-resistant Acinetobacter baumannii infections.

In this study, the activity of meropenem (MEM), fosfomycin (FOF) and polymyxin B (PMB), alone and in combination, was analysed. In addition, optimisation of the pharmacodynamic index of MEM and FOF against six isolates of OXA-23-producing Acinetobacter baumannii (including three resistant to PMB) that were not clonally related was assessed. Antimicrobial combinations were evaluated by chequerboard analysis and were considered synergistic when the fractional inhibitory concentration index (FICI) was ≤0.5. Pharmacodynamic analyses of the MEM and FOF dosing schemes were performed by Monte Carlo simulation. The target pharmacodynamic index (%ƒT>MIC) for MEM and FOF was ≥40% and ≥70%, respectively, and a probability of target attainment (PTA) ≥0.9 was considered adequate. Among the PMB-resistant isolates, combinations of PMB+MEM and PMB+FOF+MEM showed the highest synergistic activity (FICI ≤0.125); isolates that were previously PMB-resistant were included in the susceptible category using CLSI interpretive criteria. Pharmacodynamic evaluation found that for a FOF minimum inhibitory concentration (MIC) of ≤16µg/mL, treatment both by bolus dosing and prolonged infusion achieved adequate PTA, whilst for MIC=32µg/mL only infusion achieved adequate PTA. For a MEM MIC of 4µg/mL, only the bolus treatment scheme with 1.5g q6h and the infusion schemes with 1.0g q8h, 1.5g q6h and 2.0g q8h achieved PTA ≥0.9. Results of antimicrobial and pharmacodynamic analyses can assist in treating infections caused by multidrug-resistant A. baumannii. However, in vivo clinical studies are essential to evaluate the true role of these compounds, including intravenous antimicrobial FOF therapy.

The use of asymmetric distributions in average bioequivalence.

Generic drugs have been commercialized in numerous countries. Most of these countries approve the commercialization of a generic drug when there is evidence of bioequivalence between the generic drug and the reference drug. Generally, the pharmaceutical industry is responsible for the bioequivalence test under the supervision of a regulatory agency. This procedure is concluded after a statistical data analysis. Several agencies adopt a standard statistical analysis based on procedures that were previously established. In practice, we face situations in which this standard model does not fit to some sets of bioequivalence data. In this study, we propose an evaluation of bioequivalence using univariate and bivariate models based on an extended generalized gamma distribution and a skew-t distribution, under a Bayesian perspective. We introduce a study of the empirical power of hypothesis tests for univariate models, showing advantages in the use of an extended generalized gamma distribution. Three sets of bioequivalence data were analyzed under these new procedures and compared with the standard model proposed by the majority of regulatory agencies. In order to verify that the asymmetrical distributions are usually better fitted for the data, when compared with the standard model, model discrimination methods were used, such as the Deviance Information Criterion (DIC) and quantile-quantile plots. The research concluded that, in general, the use of the extended generalized gamma distribution may be more appropriate to model bioequivalence data in the original scale. Copyright © 2016 John Wiley & Sons, Ltd.

The exponentiated exponential mixture and non-mixture cure rate model in the presence of covariates.

This paper presents estimates for the parameters included in long-term mixture and non-mixture lifetime models, applied to analyze survival data when some individuals may never experience the event of interest. We consider the case where the lifetime data have a two-parameters exponentiated exponential distribution. The two-parameter exponentiated exponential or the generalized exponential distribution is a particular member of the exponentiated Weibull distribution introduced by [31]. Classical and Bayesian procedures are used to get point and confidence intervals of the unknown parameters. We consider a general survival model where the scale, shape and cured fraction parameters of the exponentiated exponential distribution depends on covariates.

The Lindley distribution applied to competing risks lifetime data.

Competing risks data usually arises in studies in which the death or failure of an individual or an item may be classified into one of k ≥ 2 mutually exclusive causes. In this paper a simple competing risks distribution is proposed as a possible alternative to the Exponential or Weibull distributions usually considered in lifetime data analysis. We consider the case when the competing risks have a Lindley distribution. Also, we assume that the competing events are uncorrelated and that each subject can experience only one type of event at any particular time.