Log-normal Survival Model Research Articles

Survival Analysis of Students’ Dropout in a Nigerian University System

Formal education remains the vehicle for socio-economic development and social mobilization in any society. Academic institutions are increasingly interested in monitoring the performance of their students. This interest has given rise to the need for research, collation, analysis, and interpretation of data to formulate evidence-based academic policies that aim to improve student performance and reduce dropout rates. Data obtained from the university comprises of Gender, Age at Entry, Marital Status, Sponsorship, Mode of Entry, Program of Study and Cumulative Grade Point Average (CGPA). This study investigated how these factors influence students’ dropout at Modibbo Adama University, Yola Adamawa State Nigeria. Survival analysis was carried out using Log-logistic, Lognormal, Weibull and Cox Proportional Hazard models. The lognormal survival model was judged as the best model due to its lowest AIC value of 1199.773. The Gender, CGPA and students’ program of study have significant effect on student dropout. Also, it was observed that 41.42% of male students dropped out when compared to 38.94% female students dropped out before their graduation year. Of all the programs of study considered, Physics has the highest number of dropped out before graduation. It accounted for 68.75%. In terms of academic performance, majority (85.05%) students who had CGPA of third class at the beginning of their studies dropped out before expected years of graduation. The study recommends that government and university management provide financial support to assist the male students who are on self-sponsorship, as financial pressure may contribute to their dropout rates

Neonatal outcomes of preterm neonates and its predictors in Ethiopian public hospitals: Multicenter prospective follow-up study

IntroductionPreterm birth remains the most significant clinical and public health encounter. Preterm infant outcomes pose key evidence for clinicians and policymakers and are extensively used to set clinical and policy verdicts to improve services. It is necessary to conduct the outcomes of neonates frequently, as it varies from place to place and even from time to time in a similar place. There is limited literature in Ethiopia about preterm neonates’ outcomes and their predictors. ObjectiveThis study aimed to assess the neonatal outcomes of preterm neonates and their predictors in South Gondar zone public hospitals, Northwest Ethiopia, 2021. MethodsA prospective observational study was employed on 462 preterm neonates in South Gondar Zone Public Hospitals. The data were entered into Epidata 4.6 and analyzed using STATA version 16/MP software. A parametric log-normal survival model was used to identify possible predictors for preterm neonate death. Statistical significance was declared at a P-value less than 0.05. ResultThe overall preterm survival rate was 71.1% (95% CI: 66.7, 75.1). Thirty-six percent of preterm neonates were diagnosed with sepsis. One-fourth of the neonates had respiratory distress syndrome. Gestational age greater than 34 weeks (β = 1.04; 95% CI: 0.53, 1.56), respiratory distress syndrome (β = 0.85; 95% CI: 0.49, 1.22), body mass index (β = −1.34; 95% CI: −1.87, −0.80), non-union marital status (β = −0.71; 95% CI: −1.34, −0.09), multiple pregnancies (β = −0.66; 95% CI: −0.99–0.32), multiparous (β = 0.35; 95% CI: 0.01, 0.69), hypothermia (β = −1.19; 95% CI: −1.76, −0.62), Kangaroo Mother Care (β = −1.9; 95% CI: −2.34, −1.41) and non-cephalic presentation (β = −1.23; 95% CI: −1.99,-0.46) were significant predictors. ConclusionIn this study, the preterm survival rate was low. Gestational age greater than 34 weeks, no respiratory distress syndrome, and multiparous mothers were positively associated with the survival of preterm neonates. Though, high pre-pregnancy maternal body mass index, non-union marital status of mothers, multiple pregnancies, hypothermia, Kangaroo mother care is not given, and non-cephalic presentation were negatively associated. A significant focus should be given to implementing WHO recommendations on preventing and caring for preterm births.

Plasma Soluble Urokinase Plasminogen Activator Receptor (suPAR) and CKD Progression in Children

Soluble urokinase plasminogen activator receptor (suPAR) is a novel biomarker associated with incident chronic kidney disease (CKD) and has been identified as an independent risk factor for CKD progression in children, although these findings remain preliminary, limited to a single point in time, and unreplicated in pediatric cohorts. Prospective longitudinal cohort study. 565 participants aged 1 to 16 years enrolled in the Chronic Kidney Disease in Children (CKiD) Study. Plasma suPAR levels, categorized by quartiles, measured at study entry and a 6-month follow-up interval. CKD progression, defined as the initiation of kidney replacement therapy (dialysis or transplantation) or >50% decline in estimated glomerular filtrate rate (eGFR). Associations between plasma suPAR quartiles and risk for CKD progression were estimated using lognormal survival models, adjusting for potential confounders. Participants in the highest suPAR quartile experienced 54% faster progression compared with the lowest quartile after adjustment for demographic and traditional CKD risk factors (P< 0.001). Addition of eGFR to the model attenuated the risk, although those in the highest quartile experienced 33% faster progression compared with the lowest quartile (P= 0.008). Plasma suPAR levels showed little change over 6 months. Potential for residual confounding, reliance on observational data, relatively fewer patients with higher eGFRs for subgroup analysis. Higher suPAR levels are associated with shorter time to kidney replacement therapy or halving of eGFR in children with CKD. This association is attenuated slightly with inclusion of eGFR in regression modeling but remains a significant association for participants with the highest suPAR levels.

Nomogram construction for predicting survival of patients with non-small cell lung cancer with malignant pleural or pericardial effusion based on SEER analysis of 10,268 patients.

Determining the accurate outcome of patients with non-small cell lung cancer (NSCLC) and malignant pleural effusion (MPE) or malignant pleural pericardial effusion (MPCE) at the initial diagnosis remains a challenge. The aim of the present study was to develop an effective nomogram for individualized estimation of overall survival in these patients. Patients diagnosed between January 2010 and December 2015 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Age, race, sex, grade, histology, laterality, stage and status of MPE or MPCE at initial diagnosis were included as covariates. Several survival models were created and the performance of each was evaluated. The most effective model was then validated by internal bootstrap resampling and by using an independent external cohort. A nomogram was created based on this survival model and the predictive accuracy of the nomogram was evaluated by calibration plots. Data from 10,268 patients with lung cancer with MPE or MPCE at initial diagnosis were collected. The multivariate analysis with a lognormal model suggested that age, race, sex, histology, stage and status of MPE or MPCE at initial diagnosis were significant independent factors to predict survival. A nomogram was constructed based on the lognormal survival model, which showed the best performance. The concordance index of the survival model in the SEER cohort was 0.736. Both internal and external validation showed an acceptable level of agreement between the nomogram-predicted survival probability and actual survival. The nomogram of the present study based on a large cohort from the SEER database may improve prognostic prediction of patients with NSCLC with MPE or MPCE at initial diagnosis, and allow physicians to make appropriate decisions for disease management of their patients.

Development and validation of a nomogram for survival benefit of lymphadenectomy in resected gallbladder cancer.

Due to absence of large, prospective, randomized, clinical trial data, the potential survival benefit of lymphadenectomy with different number of regional lymph nodes (LNs) remains controversial. We aim to create a predicting model to help estimate individualized potential survival benefit of lymphadenectomy with more regional LNs for patients with resected gallbladder cancer (GBC). Patients with resected GBC were selected from the Surveillance, Epidemiology, and End Results database who were diagnosed between 2004 and 2014. Covariates included age, race, sex, grade, histological stage, tumor sizes and receipt of non-primary surgery. Two types of multivariate survival regression models were constructed and compared. The best model performance was tested by the external validation data from our hospital. A total of 1,669 patients met the inclusion criteria for this study. The lognormal survival model showed the best performance and was tested by the external validation data, including 193 patients with resected GBC from our hospital. Nomograms, which based on the accelerated failure time parametric survival model, were built to estimate individualized survival. C-index, was up to 0.754 and 0.710 in internal validation for more and less regional LNs removed, respectively. Both of internal and external calibration curves showed good agreement between predicted and observed outcomes in the 1-, 3-, and 5-year overall survival (OS). A predicting model can be used as a decision model to predict which patients may obtain benefit from lymphadenectomy with more regional LNs.

Survival analysis of liver cirrhosis patients after transplantation using accelerated failure time models

Introduction: Liver transplantation is known as the only treatment for advanced liver cirrhosis. Considering the importance of identifying the factors affecting the survival of cirrhosis patients after transplantation in order to improve the health of these patients and increase their longevity, this study was conducted to fit the best accelerated failure time model for survival analysis of cirrhosis patients.&#x0D; Methods: This descriptive-analytical study was conducted by collecting the information about 563 patients with liver cirrhosis who underwent liver transplantation in Imam Khomeini Hospital during 2002-2013 and were followed up for at least 5 years. The data were analyzed using Chisquare test, ANOVA, and Kaplan-Meier non-parametric method as well as exponential Accelerated Failure Time, Weibull, Log-Normal, and Log-Logistic survival models.&#x0D; Results: During the study, 92 (16.3%) of the 563 patients under study died and 165 (29.3%) of them suffered liver transplant rejection. The one-year, three-year, and five-year survival of the patients after transplantation was 0.804, 0.653, and 0.420, respectively. Among the fitted Accelerated Failure Time models, the fitted log-logistic model was the most effective (P-value &lt; 0.001). The effective variables in the Multiple regression log-logistic model included bilirubin (P-value &lt; 0.001), INR (P-value &lt; 0.001), creatinine (P-value &lt; 0.001), and white blood cell (P-value = 0.011) logarithms.&#x0D; Conclusion: Regarding the results of the study, bilirubin, INR, creatinine, and white blood cell logarithmic variables were effective in the survival analysis of the patients after liver transplantation. The survival of these patients can be enhanced through necessary care to maximally control these variables.&#x0D;

Market approval of phytosanitary active substances in Europe: An empirical duration analysis

The aim of this paper is to analyze empirically the main determinants of delays to market approval of active substances in Europe. An interesting feature of this regulation is that it is based on both a decentralized examination by the rapporteur country and a centralized examination by the European Food Safety Authority (EFSA). Our econometric analysis is based on standard survival and competing risks models. The data cover 393 active substances reviewed between 1993 and 2013.We show that the review process is affected by regulatory factors, the characteristics of the active substances and the characteristics of agri-chemical firms. Log-logistic and log-normal survival models are the preferred parametric specifications, and the results suggest that the hazard function is non-monotonic over time.

Gestational age at first antenatal visit in Namibia.

To examine the relationship between pregnancy intention and gestational age at first antenatal visit in Namibia. This study uses secondary data from the 2013 Namibia Demographic and Health Survey (NDHS). Log-normal survival models are used to examine the independent effect of pregnancy intention on gestational age at first antenatal visit while controlling for relevant sociodemographic and socioeconomic covariates. This study finds that those who indicated unwanted pregnancies were significantly more likely to delay initiating antenatal care (ANC). Other variables also associated with gestational age at first antenatal visit include contact with a health worker, health insurance, media exposure to safe motherhood messages, birth order, relationship with head of household, maternal education, and urban residence. Timely ANC is necessary to identify and mitigate risk factors in pregnancy but many mothers in Namibia do not receive such care. Reducing unwanted pregnancies through family planning may limit ANC delays. After unwanted pregnancies occur, women may benefit from further education and resources that empower them to pursue ANC promptly.

Time to Neurological Deterioration in Ischemic Stroke.

Neurological deterioration (ND) is common, with nearly one-half of ND patients deteriorating within the first 24 to 48 hours of stroke. The timing of ND with respect to ND etiology and reversibility has not been investigated. At our center, we define ND as an increase of 2 or more points in the National Institutes of Health Stroke Scale (NIHSS) score within 24 hours and categorize etiologies of ND according to clinical reversibility. ND etiologies were considered non-reversible if such causes may have produced or extended any areas of ischemic neurologic injury due to temporary or permanent impairment in cerebral perfusion. Seventy-one of 350 ischemic stroke patients experienced ND. Over half (54.9%) of the patients who experienced ND did so within the 48 hours of last seen normal. The median time to ND for non-reversible causes was 1.5 days (IQR 0.9, 2.4 days) versus 2.6 days for reversible causes (IQR 1.4, 5.5 days, p=0.011). After adjusting for NIHSS and hematocrit on admission, the log-normal survival model demonstrated that for each 1-year increase in a patient's age, we expect a 3.9% shorter time to ND (p=0.0257). In addition, adjusting for age and hematocrit on admission, we found that that for each 1-point increase in the admission NIHSS, we expect a 3.1% shorter time to ND (p=0.0034). We found that despite having similar stroke severity and age, patients with nonreversible causes of ND had significantly shorter median time to ND when compared to patients with reversible causes of ND.

Anticoagulation Management Practices and Outcomes in Elderly Patients with Acute Venous Thromboembolism: A Clinical Research Study.

Whether anticoagulation management practices are associated with improved outcomes in elderly patients with acute venous thromboembolism (VTE) is uncertain. Thus, we aimed to examine whether practices recommended by the American College of Chest Physicians guidelines are associated with outcomes in elderly patients with VTE. We studied 991 patients aged ≥65 years with acute VTE in a Swiss prospective multicenter cohort study and assessed the adherence to four management practices: parenteral anticoagulation ≥5 days, INR ≥2.0 for ≥24 hours before stopping parenteral anticoagulation, early start with vitamin K antagonists (VKA) ≤24 hours of VTE diagnosis, and the use of low-molecular-weight heparin (LMWH) or fondaparinux. The outcomes were all-cause mortality, VTE recurrence, and major bleeding at 6 months, and the length of hospital stay (LOS). We used Cox regression and lognormal survival models, adjusting for patient characteristics. Overall, 9% of patients died, 3% had VTE recurrence, and 7% major bleeding. Early start with VKA was associated with a lower risk of major bleeding (adjusted hazard ratio 0.37, 95% CI 0.20–0.71). Early start with VKA (adjusted time ratio [TR] 0.77, 95% CI 0.69–0.86) and use of LMWH/fondaparinux (adjusted TR 0.87, 95% CI 0.78–0.97) were associated with a shorter LOS. An INR ≥2.0 for ≥24 hours before stopping parenteral anticoagulants was associated with a longer LOS (adjusted TR 1.2, 95% CI 1.08–1.33). In elderly patients with VTE, the adherence to recommended anticoagulation management practices showed mixed results. In conclusion, only early start with VKA and use of parenteral LMWH/fondaparinux were associated with better outcomes.

Bayesian Analysis of Parametric Survival Models: A Computer Simulation Study based Informative Priors

In the article, the performance of Bayesian parametric survival models (Weibull, exponential, log-normal and log-logistic) by using Monte Carlo simulation was empirically compared while varying the informative priors and the sample sizes. We simulated the generated data by running for each of Weibull, exponential, log-normal and log-logistic survival models under varying informative priors and sample sizes using our simulation algorithm. For each situation, 1000 simulations were performed. Models with proper informative prior showed a good performance with too little bias. It was found out that bias of models increased while priors were becoming distant from reliability in all sample sizes. According to results obtained from simulation study, researchers should avoid assessment of data by using only one parametric survival model in future studies. We suggest that data should be better explored and processed by high performance modelling methods. Especially, quality of prior information to update knowledge about the parameters was a very important.

Gestational Age at First Antenatal Care Visit in Malawi.

This paper examines the gestational age at first antenatal care (ANC) visit and factors associated with timely initiation of ANC in Malawi in a context where maternal and child health services are generally provided for free. Lognormal survival models are applied to Demographic and Health Survey data from a nationally representative sample of women (n = 13,588) of child-bearing age. The findings of this study show that less than 30 % of pregnant women initiate ANC within the World Health Organization recommended gestational timeframe of 16 weeks or earlier. The hazard analysis shows a gradient in the initiation of ANC by maternal education level, with least educated mothers most likely to delay their first ANC visit. However, after adjusting for variables capturing intimate partner violence in the multivariate models, the effect of maternal education attenuated and lost statistical significance. Other significant predictors of gestational age at first ANC include media exposure, perceived distance from health facility, age, and birth order. The findings of the study link domestic violence directly with the gestational age at which mothers initiate ANC, suggesting that gender-based violence may operate through delayed initiation of ANC to undermine maternal and child health outcomes.

Estimation of Multiprocess Survival Models with cmp

Multilevel multiprocess hazard models are routinely used by demographers to control for endogeneity and selection effects. These models consist of multilevel proportional hazards equations, and possibly probit equations, with correlated random effects. Although Stata currently lacks a specialized command for fitting systems of multilevel proportional hazards models, systems of seemingly unrelated lognormal survival models can be fit with the user-written cmp command (Roodman 2011, Stata Journal 11: 159–206). In this article, we describe multiprocess survival models and demonstrate theoretical and practical aspects of estimation. We also illustrate the application of the cmp command using examples related to demographic research. The examples use a dataset shipped with the statistical software aML.

Determinants of bile acids.

632 Background: Several epidemiological studies have demonstrated an association between bile acids (BA) and colorectal cancer. Despite this evidence, there are limited studies that examine the determinants of bile acids in humans. We conducted a secondary, cross-sectional analysis on 735 adenoma formers from a phase III adenoma prevention trial of ursodeoxycholic acid (URSO) who provided a fecal sample at their baseline visit. Methods: Fecal measures of primary bile acids cholic acid (CA) and chenodoxycholic acid (CDCA), as well as secondary bile acids, deoxycholic acid (DCA), lithocholic (LCA) were the outcome variables of interest. Dietary, non-dietary, medication use, genetic variation in the CYP7A1 gene (as single nucleotide polymorphisms (SNPs) and haplotypes), and physical activity, and characteristics of baseline adenoma were evaluated as correlates of fecal BAs. We used maximum likelihood methods to incorporate left-censoring in the BAs that had concentrations below the detection limit (BDL). These log-normal parametric survival models were used to fit potential predictors of fecal BA levels, stratifying by sex. The Akaike information criterion (AIC) was used to choose the best predictive model from each BA outcome. Model accuracy was assessed using leave-one-out cross validation and a likelihood-based measure of R2 and the Brier score. Results: LDL and cholesterol were predictors for primary bile acid CDCA in men and women, as was the use of pain medication (use of medication lowered BA levels). Genetic variation in CYP7A1 (as haplotypes and individual SNP's) was a significant determinant of CA level in both men and women. BMI was an important predictor for both men and women for DCA and CA. Presentation with tubular-villous histology was associated with LCA levels whereas proximal adenoma was an important predictor for CA levels, in men and women. Conclusions: This secondary analysis of a uniquely large dataset validates previous studies that suggest lifestyle and genetic factors influence colonic exposure to carcinogenic BAs. These findings also importantly highlight gender-specific differences in BA determinants that may explain colorectal cancer incidence differences between men and women.

P5-14-01: Differences in Efficacy by Assessment Method: NCIC CTG Adjuvant Breast Cancer Trials MA.5, MA.12, MA.14, MA.21, MA.27 Meta-Analysis.

Abstract Background: Based on recent breast cancer literature, we hypothesized that there could be substantive differences in apparent efficacy estimates using a log-normal (LN) survival model rather than with standard Kaplan-Meier (K-M) or Cox model methods. While both Cox and LN survival analyses offer greater specification by individual patient characteristics, the LN model may more robustly estimate survival under model misspecification. Methods: We recently pooled data for 5 NCIC CTG primary breast cancer trials: MA.5, MA.12, MA.14, MA.21, and MA.27. The total patient count for patients who received at least 1 dose of trial therapy is 11,253. Compilation included definition of STEEP endpoints (C Hudis, JCO, 2008) and standardized factor categorizations. The primary endpoint is Breast Cancer Free Interval (BCFI) defined as the time from randomization until recurrence: first local invasive or DCIS; regional, or distant; contralateral invasive or DCIS; or death from breast cancer. We found substantive evidence of non-proportionality for 7 factors compiled for the meta-analyses. In this work, we fit multivariate Cox and LN models with these 7 factors, lymph node status and pathologic T status. We then compare BCFI efficacy estimates for patient and tumour characteristics at 1-, 3-, and 5-years obtained with K-M, Cox, and LN models. Results: There was evidence that the Cox assumption of proportional hazards was violated for 7 factors: age, menopausal status, hormone receptor status, anthracycline use, chemotherapy use, race, and ECOG performance status. Differences between models were intrinsically affected by timing and extent of non-proportionality; there was no consistent pattern. In particular, investigations to date indicate efficacy estimates with absolute differences between K-M, Cox and LN estimates which varied by time of assessment: at 1-year 0.0 to 6.7%, at 3-years 0.4 to 18.6%, and at 5-years 0.2 to 17.0%. BCFI estimates with the K-M were inconsistently closer to those with the LN or Cox model: for K-M to Cox at 1-year 0.4 to 5.2%, at 3-years 0.4 to 15%, at 5-years 0.4 to 14.3%; for K-M to LN at 1-year 0.0 to 6.7%, at 3-years 0.5 to 18.6%, at 5-years 0.2 to 17.0%; for Cox to LN at 1-year 0.8 to 1.8%, at 3-years 1.9 to 6.0%, at 5-years 0.6 to 5.7%. K-M and Cox models have step-wise adjustments at events for K-M and Cox, rather than smooth modeling with the LN. Discussion: Even with reasonably large population subgroups, there were substantive differences in apparent survival (0.0 to 18.6%) between K-M, Cox and LN model types. The magnitude of differences in survival estimates was large enough to be clinically relevant and warrant further consideration as we evaluate new therapies and prognostic/predictive factors. We will be statistically investigating framework robustness under differing levels of model misspecification. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P5-14-01.

Nomogram for predicting the benefit of adjuvant chemoradiotherapy for resected gallbladder cancer.

Although adjuvant chemoradiotherapy for resected gallbladder cancer may improve survival for some patients, identifying which patients will benefit remains challenging because of the rarity of this disease. The specific aim of this study was to create a decision aid to help make individualized estimates of the potential survival benefit of adjuvant chemoradiotherapy for patients with resected gallbladder cancer. Patients with resected gallbladder cancer were selected from the Surveillance, Epidemiology, and End Results (SEER) -Medicare database who were diagnosed between 1995 and 2005. Covariates included age, race, sex, stage, and receipt of adjuvant chemotherapy or chemoradiotherapy (CRT). Propensity score weighting was used to balance covariates between treated and untreated groups. Several types of multivariate survival regression models were constructed and compared, including Cox proportional hazards, Weibull, exponential, log-logistic, and lognormal models. Model performance was compared using the Akaike information criterion. The primary end point was overall survival with or without adjuvant chemotherapy or CRT. A total of 1,137 patients met the inclusion criteria for the study. The lognormal survival model showed the best performance. A Web browser-based nomogram was built from this model to make individualized estimates of survival. The model predicts that certain subsets of patients with at least T2 or N1 disease will gain a survival benefit from adjuvant CRT, and the magnitude of benefit for an individual patient can vary. A nomogram built from a parametric survival model from the SEER-Medicare database can be used as a decision aid to predict which gallbladder patients may benefit from adjuvant CRT.

Temporal Trends in Highly Active Antiretroviral Therapy Initiation among Injection Drug Users in Baltimore, Maryland, 1996–2008

We characterized temporal trends in highly active antiretroviral therapy (HAART) initiation (1996-2008) among treatment-eligible persons in a community-based cohort of current and former injection drug users (IDUs) in Baltimore, Maryland. The AIDS Linked to the IntraVenous Experience (ALIVE) cohort has been observing human immunodeficiency virus (HIV)-positive IDUs since 1988. HAART eligibility was defined as the first visit after 1 January 1996 at which the patient's CD4(+) cell count was <350 cells/microL. Temporal trends and predictors of HAART initiation were examined using chi(2) tests for trend and lognormal survival models. The median age of 582 HAART-eligible IDUs was 41 years; 75% of the subjects were male, 97% were African American, and 60% were active IDUs. Of these 582 individuals, 345 initiated HAART over 1803 person-years (19.2 subjects per 100 person-years; 95% confidence interval, 17.2-21.3 subjects per 100 person-years); there was no statistically significant temporal trend in HAART initiation. Independent predictors of delayed initiation included heavy injection drug use; having a prior AIDS diagnosis, having a lower CD4(+) cell count, having a usual source of care, and having health insurance were predictors of more-rapid initiation. The delay between eligibility and initiation decreased among those who became eligible most recently (2003-2007), compared with those in earlier periods (1996-2002); however, a substantial number of patients who became eligible in recent years either initiated HAART after a substantial delay or did not initiate HAART at all. We failed to observe substantial improvement in HAART initiation among current and former IDUs over a 12-year period; heavy use of injection drugs remains the major barrier to HAART initiation and to consistent HIV care. The fact that many IDUs initiate HAART after a significant delay or do not initiate it at all raises concern that disparities in HIV care for IDUs remain at a time of simplified antiretroviral regimens and increasing adoption of earlier treatment.

The prognosis of a normal stress-only Tc-99m myocardial perfusion imaging study

BackgroundStress-only imaging saves time and radiation exposure, but apprehension remains about the reliability, diagnostic, and prognostic accuracy of a normal stress-only study. The objective of this study was to determine the prognosis of stress-only SPECT MPI in routine clinical practice. MethodsPatients at lower pre-test risk for CAD presenting for a Tc-99m SPECT MPI over a 2-year period underwent a stress-only protocol. If the stress images were normal (attenuation correction was routinely acquired on all patients), rest imaging was not done. Outcomes of the stress-only group were compared to a full rest-stress protocol cohort. Only patients with normal perfusion and left ventricular function, and no known CAD, were included. All-cause mortality was determined using the Social Security Death Index and specific causes of death were determined using the National Death Index. The difference in all-cause and cardiac mortality between groups in the presence of competing risks was assessed using log-normal survival models. ResultsOut of 10,609 patients studied during the time period, 1,673 had a normal stress-only study and 3,237 had a normal rest-stress study. At one year, there were 20 total and 3 cardiac deaths (1.2% and 0.2% mortality) in the stress-only group, and 40 total and 4 cardiac deaths (1.2% and 0.1% mortality) in the rest-stress cohort. At the end of follow-up (40 ± 9 months), there were 46 total and 7 cardiac deaths (2.7% and 0.4% mortality) in the stress-only group, and 119 total and 17 cardiac deaths (3.7% and 0.5% mortality) in the rest-stress cohort. No significant difference between the stress-only and rest-stress cohorts was found after controlling for confounding variables for both all-cause mortality (p = .94) and cardiac mortality (p = .82). ConclusionsA normal stress-only MPI has an excellent short-term prognosis (both for all-cause and cardiac mortality) comparable to that of a normal rest-stress MPI study.

Valuation of the Economic Benefits of Human Papillomavirus Vaccine in Taiwan

The study aims to apply the contingent valuation method to elicit the willingness-to-pay (WTP), and measure the value of a statistic life (VSL), for human papillomavirus (HPV) vaccine in Taiwan. A total of 512 questionnaires were completed on women aged 20 to 55 years with at least one daughter, during March through May 2007. The respondents' WTP for the vaccines was elicited by double-bounded binary-choice questions under two scenarios: one was to protect themselves from cervical cancer (CC) and the other was for their daughter(s). The WTP was modeled as a function of the respondents' knowledge score, attitudes toward CC and HPV vaccine, the vaccination outcome scenarios, and individual characteristics. A log-normal survival model was constructed and the maximum-likelihood method was used for estimation. The median regression-adjusted WTP was estimated at US$1098 to US$1233 (US$913-1004) for vaccinating the daughter (mother); and the VSL was estimated at approximately US$0.65 to US$4.09 (US$0.56-3.16) million for vaccinating the daughter (mother). The study results provided important evidences on the monetary value women placed on a HPV vaccine, and the differential benefits between vaccinating the women and their daughters.

A survival analysis of the approval of US patent applications

We model the length of time that it takes for a patent application to be granted by the US Patent and Trademark Office (USPTO), conditional on the patent actually being awarded eventually. Survival analysis is applied and both the nonparametric Kaplan–Meier and parametric accelerated failure time models are used to analyse the data. We find that the number of claims a patent makes, the number of citations a patent makes, the patent's technological category, and the type of applicant all have significant effects on the duration that a patent is under consideration. A log-normal survival model is the preferred parametric specification, and the results suggest that the hazard function is nonmonotonic over time.