Transdermal scopolamine for the treatment of recurrent parotid sialocele: a case report.

Recurrent parotid sialocele is rare and challenging to treat. Treatment options are limited for cases of parotid sialocele that recur despite ductal ligation. This case study presents a patient who underwent wide excision of the right buccal mucosa due to squamous cell carcinoma. During the wide excision, a segment of the parotid duct was excised, and ductal ligation was performed to prevent the occurrence of a sialocele, followed by reconstruction using a folded anterolateral thigh free flap. Twenty-two days after surgery, parotid sialocele occurred despite the initial ductal ligation and subsequent ductal ligation was performed; however, the sialocele recurred. As an alternative therapeutic option, a transdermal scopolamine patch was applied for 3 weeks, with one patch used every 3 days. The results were encouraging, with complete resolution of the sialocele. A transdermal scopolamine offers a noninvasive, convenient method of treating parotid sialocele with minimal side effects. The successful outcome of this case suggests that a transdermal scopolamine can be an effective therapeutic option for recurrent parotid sialocele in conjunction with surgical treatment.

Nutrient Density, Added Sugar, and Fiber Content of Commercially Available Fruit Snacks in the United States from 2017 to 2022.

Fruit snacks have become a popular and convenient snacking choice and have the potential to contribute to a well-balanced diet. However, the nutritional quality of fruit snack products has not yet been studied. The objective of the present study is to provide a nutritional assessment of the fruit snack product category. This study used the Mintel Global New Product Database to collect data about fruit snack products launched in the United States from 2017 to 2022. Fruit snack products (n = 2405) are divided into nine product categories based on product characteristics. Nutrition composition was assessed using a comprehensive score, Nutrient Rich Food (NRF) model, and by examining individual components (added sugar and fiber). The results show that dried fruit has the highest nutrient density, fiber content, and the lowest added sugar content. Conversely, fruit-flavored snacks have the lowest nutrient density, fiber content, and added sugar content. Currently, fruit puree, canned fruit with juice, and dried fruit are the only fruit snacks that meet the current recommendations set by the USDA Dietary Guidelines. Future directions for the fruit snack category should consider decreasing the added sugar content, increasing the fiber content, and enhancing their sensory profile to improve the overall nutrient density.

Identifying Trajectories of Maltreatment Revictimization and Juvenile Justice Outcome: A Latent Class Analysis of Subtype, Timing, and Chronicity.

Continued exposure to abuse or neglect is a strong predictor for immediate and long-term negative developmental outcomes including developmental delays, disabilities, poor school performance, criminal behavior, and mental health issues. The purpose of this study was to identify distinct subgroups of children with repeat victimization based on maltreatment timing, subtype, and chronicity and to examine how the unique subgroups are related to youth's juvenile justice outcome. Using data from Longitudinal Studies of Child Abuse and Neglect, this study included 286 children (47% males, 41% blacks) with more than one report for substantiated maltreatment from birth to age 17. Latent class analysis was employed to identify heterogeneity in the patterns of maltreatment revictimization. Four latent classes emerged: (a) Prevailing Early Neglect (52.6%); (b) Co-occurring Maltreatments in Preschool Age (20.1%); (c) Incremental Neglect with Sexual Abuse in School Age (18.7%); and (d) Co-occurring Maltreatments in School Age (8.6%). Black children were overrepresented in Incremental Neglect with Sexual Abuse in School Age compared to white and other racial groups of children. Ordinal logistic regression analysis indicated that there was no significant difference in the juvenile justice outcome across four subgroups of children with revictimization. Our person-centered investigations of maltreatment subtype, timing, and chronicity highlight the need for precise assessment and prevention strategies based on a more nuanced understanding of various patterns of childhood maltreatment revictimization.

Nasal Iodophor Antiseptic vs Nasal Mupirocin Antibiotic in the Setting of Chlorhexidine Bathing to Prevent Infections in Adult ICUs: A Randomized Clinical Trial.

Importance: Universal nasal mupirocin plus chlorhexidine gluconate (CHG) bathing in intensive care units (ICUs) prevents methicillin-resistant Staphylococcus aureus (MRSA) infections and all-cause bloodstream infections. Antibiotic resistance to mupirocin has raised questions about whether an antiseptic could be advantageous for ICU decolonization. Objective: To compare the effectiveness of iodophor vs mupirocin for universal ICU nasal decolonization in combination with CHG bathing. Design, Setting, and Participants: Two-group noninferiority, pragmatic, cluster-randomized trial conducted in US community hospitals, all of which used mupirocin-CHG for universal decolonization in ICUs at baseline. Adult ICU patients in 137 randomized hospitals during baseline (May 1, 2015-April 30, 2017) and intervention (November 1, 2017-April 30, 2019) were included. Intervention: Universal decolonization involving switching to iodophor-CHG (intervention) or continuing mupirocin-CHG (baseline). Main Outcomes and Measures: ICU-attributable S aureus clinical cultures (primary outcome), MRSA clinical cultures, and all-cause bloodstream infections were evaluated using proportional hazard models to assess differences from baseline to intervention periods between the strategies. Results were also compared with a 2009-2011 trial of mupirocin-CHG vs no decolonization in the same hospital network. The prespecified noninferiority margin for the primary outcome was 10%. Results: Among the 801 668 admissions in 233 ICUs, the participants' mean (SD) age was 63.4 (17.2) years, 46.3% were female, and the mean (SD) ICU length of stay was 4.8 (4.7) days. Hazard ratios (HRs) for S aureus clinical isolates in the intervention vs baseline periods were 1.17 for iodophor-CHG (raw rate: 5.0 vs 4.3/1000 ICU-attributable days) and 0.99 for mupirocin-CHG (raw rate: 4.1 vs 4.0/1000 ICU-attributable days) (HR difference in differences significantly lower by 18.4% [95% CI, 10.7%-26.6%] for mupirocin-CHG, P < .001). For MRSA clinical cultures, HRs were 1.13 for iodophor-CHG (raw rate: 2.3 vs 2.1/1000 ICU-attributable days) and 0.99 for mupirocin-CHG (raw rate: 2.0 vs 2.0/1000 ICU-attributable days) (HR difference in differences significantly lower by 14.1% [95% CI, 3.7%-25.5%] for mupirocin-CHG, P = .007). For all-pathogen bloodstream infections, HRs were 1.00 (2.7 vs 2.7/1000) for iodophor-CHG and 1.01 (2.6 vs 2.6/1000) for mupirocin-CHG (nonsignificant HR difference in differences, -0.9% [95% CI, -9.0% to 8.0%]; P = .84). Compared with the 2009-2011 trial, the 30-day relative reduction in hazards in the mupirocin-CHG group relative to no decolonization (2009-2011 trial) were as follows: S aureus clinical cultures (current trial: 48.1% [95% CI, 35.6%-60.1%]; 2009-2011 trial: 58.8% [95% CI, 47.5%-70.7%]) and bloodstream infection rates (current trial: 70.4% [95% CI, 62.9%-77.8%]; 2009-2011 trial: 60.1% [95% CI, 49.1%-70.7%]). Conclusions and Relevance: Nasal iodophor antiseptic did not meet criteria to be considered noninferior to nasal mupirocin antibiotic for the outcome of S aureus clinical cultures in adult ICU patients in the context of daily CHG bathing. In addition, the results were consistent with nasal iodophor being inferior to nasal mupirocin. Trial Registration: ClinicalTrials.gov Identifier: NCT03140423.

Event history analysis on racial disparities in the path to adoption for Black and White children.

BACKGROUND: Black children are significantly overrepresented in many phases of the U.S. child welfare system. OBJECTIVE: The purpose of this study is to investigate racial disproportionality and disparities in the adoption process and factors that predict the length of time to adoption. PARTICIPANTS AND SETTING: This study utilized administrative data from the 2014 year of the Adoption and Foster Care Analysis and Reporting System (AFCARS) collected in 50 States, the District of Columbia, and Puerto Rico. METHODS: The disproportionality metric (DM) and disparity index (DI) were constructed for Black and White children, and event history analyses were conducted to calculate the probability of adoption while considering the time to adoption finalization. RESULTS: DM indicated that Black children (0.81) were underrepresented in adoption, and DI indicated that the likelihood of adoption for Black children (0.73) was one third lower than that for White children. The event history analyses revealed that White children were 1.27 times more likely to be adopted than Black children. White children had considerably fewer days from termination of parental rights to adoption finalization with a median time of 273.5 days compared to 328 days for Black children. Factors that extended adoption time included child intellectual, physical, and emotional/behavioral disabilities, visual and hearing impairments, parental alcohol abuse and disability, and child maltreatment histories, while parental drug abuse and longer stays in out-of-home care shortened the adoption process. We also found a significant interaction effect of race and neglect on adoption. Neglected Black children had a longer time to adoption than neglected White children. CONCLUSIONS: More dedicated outreach programs and resources must be developed to ensure the effectiveness of adoption services and cultural continuity for Black children.

The use of physical restraints and PRN medications in adolescent psychiatric inpatient units.

PROBLEM: Although physical restraint practices and psychotropic/sedative pro re neta (PRN, as needed) medications have been commonly used for managing inpatient aggression, little is known about the characteristics of adolescents who receive them in psychiatric adolescent inpatient units. We aimed to determine the relationship between the use of physical restraints and psychotropic/sedative PRN medications, and to characterize individual attributes, substance use, clinical factors, and time of the first restraint episodes of the use of physical restraints and psychotropic/sedative PRN medications. METHODS: A retrospective case-control study approach was used with the data from electronic health records at a pediatric psychiatric hospital in the United States. Descriptive statistics, χ2 , multivariate logistic regression, and Cox proportional hazard model were used. FINDINGS: Participants of younger age and participants with a longer length of stay were significantly associated with the use of physical restraints and psychotropic/sedative PRN medications, although the substance-related risks were not significantly associated with the use of restraints. Physical restraints were more likely to have occurred soon after the admission and tapered off as the length of stay increased. CONCLUSIONS: This study provides important information in understanding the risk factors of the use of restraints and psychotropic/sedative PRN medications in psychiatric adolescent inpatient units.

New Measures for Family Planning and Exposure to Risk of Pregnancy Based on Sexual Activity and Contraceptive Use Data.

Family planning measures for unmarried women are based on contraceptive demand and use among sexually active women. Sexual activity status is commonly defined based on comparing reported time-since-last-sex to a cutoff time, with women defined to be sexually active if their most recent sex was within the last four weeks. While easy to understand and compute, this approach to constructing family planning measures results in a limited understanding of family planning and exposure to unintended pregnancy because it cannot comprehensively capture the frequency of sex at the population level. We propose a new statistical approach to quantify sexual activity, using reported time-since-last-sex data. Based on estimated frequencies of sex among users and nonusers in need of family planning, we propose new family planning measures, including the ratio of protected exposure over all women's exposure to risk of unintended pregnancy.

HOW TO IDENTIFY SUBGROUPS IN LONGITUDINAL CLINICAL DATA: TREATMENT RESPONSE PATTERNS IN PATIENTS WITH A SHORTENED DENTAL ARCH.

BACKGROUND: When dental patients seek care, treatments are not always successful,that is patients' oral health problems are not always eliminated or substantially reduced. Identifying these patients (treatment non-responders) is essential for clinical decision-making. Group-based trajectory modeling (GBTM) is rarely used in dentistry, but a promising statistical technique to identify non-responders in particular and clinical distinct patient groups in general in longitudinal data sets. AIM: Using group-based trajectory modeling, this study aimed to demonstrate how to identify oral health-related quality of life (OHRQoL) treatment response patterns by the example of patients with a shortened dental arch (SDA). METHODS: This paper is a secondary data analysis of a randomized controlled clinical trial. In this trial SDA patients received partial removable dental prostheses replacing missing teeth up to the first molars (N = 79) either or the dental arch ended with the second premolar that was present or replaced by a cantilever fixed dental prosthesis (N = 71). Up to ten follow-up examinations (1-2, 6, 12, 24, 36, 48, 60, 96, 120, and 180 months post-treatment) continued for 15 years. The outcome OHRQoL was assessed with the 49-item Oral Health Impact Profile (OHIP). Exploratory GBTM was performed to identify treatment response patterns. RESULTS: Two response patterns could be identified - "responders" and "non-responders." Responders' OHRQoL improved substantially and stayed primarily stable over the 15 years. Non-responders' OHRQoL did not improve considerably over time or worsened. While the SDA treatments were not related to the 2 response patterns, higher levels of functional, pain-related, psychological impairment in particular, and severely impaired OHRQoL in general predicted a non-responding OHRQoL pattern after treatment. Supplementary, a 3 pattern approach has been evaluated. CONCLUSIONS: Clustering patients according to certain longitudinal characteristics after treatment is generally important, but specifically identifying treatment in non-responders is central. With the increasing availability of OHRQoL data in clinical research and regular patient care, GBTM has become a powerful tool to investigate which dental treatment works for which patients.

BivRec: an R package for the nonparametric and semiparametric analysis of bivariate alternating recurrent events.

BACKGROUND: Bivariate alternating recurrent event data can arise in longitudinal studies where patients with chronic diseases go through two states that occur repeatedly, e.g., care periods and break periods. However, there was no statistical software that provided tools for the analysis of such data. To meet this software need, we developed BivRec, a package for R that contains a set of tools for exploratory, nonparametric and semiparametric regression analysis of bivariate alternating recurrent events. RESULTS: The BivRec package provides functions for nonparametric estimations for the joint distribution of bivariate gap times (bivrecNP) and semiparametric regression methods for evaluating covariate effects on the two types of gap times under the accelerated failure time model framework (bivrecReg). The package also provides exploratory data analysis tools such as a visualization of the gap times by groups. We utilize a subset of the South Verona Psychiatric Case Register (PCR) data to illustrate the use of the BivRec package for the reviewed methods. CONCLUSIONS: We demonstrate BivRec's capability for data visualization, nonparametric and regression based analysis, as well as data simulation. The package has default methods with satisfactory performance despite the complexity of calculations and fills a gap in software for statistical analysis of bivariate alternating recurrent events. BivRec is accessible under the GPL-3 General Public License through CRAN, facilitating its installation.

Is assessment of oral health-related quality of life burdensome? An item nonresponse analysis of the oral health impact profile.

AIM: This study aimed to investigate if in the 49-item Oral Health Impact Profile (OHIP): (i) more missing data occurred when participants answered more questions, (ii) more missing data occurred in a particular item or set of related items, and (iii) item missingness was associated with the demographic characteristics and oral health-related quality of life (OHRQoL) impairment level. METHODS: We used OHIP data from the Dimensions of OHRQoL (DOQ) project, which consolidated data from 35 individual studies. Among these studies, we analyzed OHIP data from 19 studies (4,847 surveyed individuals, of which 3,481 were completed under supervision and 1,366 were completed unsupervised) that contained some missing information. We computed descriptive statistics to investigate the OHIP missingness. We also used logistic regression analyses, with missing information as the dependent variable, and number of questions filled in (OHIP item rank) as the independent variable for samples with and without supervision. To investigate whether missing data occurs more in a particular item or set of related items we fitted regression models with individual OHIP items and the OHRQoL dimensions as indicator variables. We also investigated age, gender, and OHRQoL level as predictor variables for missing OHIP items. RESULTS: We found very low levels of missingness across individual OHIP items and set of related items, and there was no particular item or set of related items that was associated with more missing data. Also, more missing data did not depend on whether the participants answered more questions. In studies without supervision, older persons and females were 5.47 and 2.66 times more likely to have missing items than younger persons and females. However, in studies with supervision, older persons, and participants with more OHRQoL impairment were 1.70 and 2.65 times more likely to have missing items. CONCLUSION: The study participants from general and dental patient populations did not find OHIP-49 burdensome. OHIP item missingness did not depend on a particular OHIP item or set of related items, or if the study participants responded to a greater number of OHIP items. We did not find a consistent pattern of the influence of sociodemographic and OHRQoL magnitude information on OHIP missingness. The amount of missing OHIP information was low making any potential influence likely small in magnitude.

CoxPhLb: An R Package for Analyzing Length Biased Data under Cox Model.

Data subject to length-biased sampling are frequently encountered in various applications including prevalent cohort studies and are considered as a special case of left-truncated data under the stationarity assumption. Many semiparametric regression methods have been proposed for length-biased data to model the association between covariates and the survival outcome of interest. In this paper, we present a brief review of the statistical methodologies established for the analysis of length-biased data under the Cox model, which is the most commonly adopted semiparametric model, and introduce an R package CoxPhLb that implements these methods. Specifically, the package includes features such as fitting the Cox model to explore covariate effects on survival times and checking the proportional hazards model assumptions and the stationarity assumption. We illustrate usage of the package with a simulated data example and a real dataset, the Channing House data, which are publicly available.

SEMIPARAMETRIC REGRESSION MODEL FOR RECURRENT BACTERIAL INFECTIONS AFTER HEMATOPOIETIC STEM CELL TRANSPLANTATION.

Patients who undergo hematopoietic stem cell transplantation (HSCT) often experience multiple bacterial infections during the early post-transplant period. In this article, we consider a semiparametric regression model that correlates patient- and transplant-related risk factors with inter-infection gap times. Existing regression methods for recurrent gap times are not directly applicable to study post-transplant infection because the initiating event (transplant) is different than the recurrent events of interest (post-transplant infections); as a result, the time from transplant to the first infection and the time elapsed between consecutive infections have distinct biological meanings and hence follow different distributions. Moreover, risk factors may have different effects on these two types of gap times. We propose a semiparametric estimation procedure to evaluate the covariate effects on time from transplant to thefirst infection and on gap times between consecutive infections simultaneously. The proposed estimator accounts for dependent censoring induced by within-subject correlation among recurrent gap times and length bias in the last censored gap time due to intercept sampling. We study the finite sample properties through simulations and present an application of the proposed method to the post-HSCT bacterial infection data collected at the University of Minnesota.

Analysis of combined incident and prevalent cohort data under a proportional mean residual life model.

The Nun Study, a longitudinal study to examine risk factors for the progression of dementia, consists of subjects who were already diagnosed with dementia (ie, prevalent cohort) and those who do not have dementia (ie, incident cohort) at study enrollment. When assessing the risk factors' effects on the survival time from dementia diagnosis until death, utilizing data from both cohorts supports more efficient statistical inference because the two cohorts provide valuable complementary information. A major challenge in analyzing the combined cohort data is that the prevalent cases are not representative of the target population. Moreover, the dates of dementia diagnosis are not ascertained for the prevalent cohort in the Nun Study. Hence, the survival time for the prevalent cohort is only partially observed from study enrollment until death or censoring, with the time from dementia diagnosis to study enrollment missing. In this paper, we propose an efficient estimation method that uses both incident and prevalent cohorts under the proportional mean residual life model. By assuming proportionality of the mean residual life time with covariates in the incident cohort, we can utilize the natural relationship between the mean residual life function and the hazard function of the survival time measured from enrollment until death for the prevalent cohort. We evaluate the efficiency gain from using the combined cohort data through simulations and demonstrate that the proposed method is valid and efficient.

Model diagnostics for the proportional hazards model with length-biased data.

Length-biased data are frequently encountered in prevalent cohort studies. Many statistical methods have been developed to estimate the covariate effects on the survival outcomes arising from such data while properly adjusting for length-biased sampling. Among them, regression methods based on the proportional hazards model have been widely adopted. However, little work has focused on checking the proportional hazards model assumptions with length-biased data, which is essential to ensure the validity of inference. In this article, we propose a statistical tool for testing the assumed functional form of covariates and the proportional hazards assumption graphically and analytically under the setting of length-biased sampling, through a general class of multiparameter stochastic processes. The finite sample performance is examined through simulation studies, and the proposed methods are illustrated with the data from a cohort study of dementia in Canada.

Combination of Prostate Cancer Antigen 3 and Prostate-Specific Antigen Improves Diagnostic Accuracy in Men at Risk of Prostate Cancer.

CONTEXT: - Prostate cancer antigen 3 (PCA3) is a noncoding RNA that is highly overexpressed in prostate cancer (PCa) tissue and excreted in urine in patients with PCa. OBJECTIVE: - To assess the clinical utility of urinary PCA3 in men at risk of PCa. DESIGN: - We retrospectively reviewed a cohort of 271 men (median age, 63 years) with elevated prostate-specific antigen (PSA), and/or strong family history, and/or abnormal digital rectal examination findings. Diagnostic sensitivity, specificity, positive and negative predictive values (PPV, NPV), positive and negative likelihood ratios (LR+, LR-), and diagnostic odds ratio (DOR), and area under the receiver-operating characteristic curves (AUC) were evaluated. RESULTS: - PCA3 score was a significant predictor of prostate biopsy outcome ( P < .001). A PCA3 score of 30 was the optimal cutoff for our study cohort, with a diagnostic sensitivity of 72.7%, specificity of 67.5%, PPV of 47.1%, NPV of 86.2%, LR+ of 2.24, LR- of 0.40, and DOR of 5.55. At this cutoff score, the PCA3 assay could avoid 57.4% of unnecessary invasive biopsies in the overall study cohort and 70.3% in the subgroup with PSA level in the "gray zone" (4-10 ng/mL). A logistic regression algorithm combining PCA3 with PSA increased the AUC from 0.571 for PSA-only to 0.729 ( P < .001). The logistic combined marker gained the ability to discriminate low-grade from high-grade cancers. CONCLUSIONS: - Our data suggest that PCA3 improves the diagnostic sensitivity and specificity of PSA and that the combination of PCA3 with PSA gives better overall performance in identification of PCa than serum PSA alone in the high-risk population.

Analysis of restricted mean survival time for length-biased data.

In clinical studies with time-to-event outcomes, the restricted mean survival time (RMST) has attracted substantial attention as a summary measurement for its straightforward clinical interpretation. When the data are subject to length-biased sampling, which is frequently encountered in observational cohort studies, existing methods to estimate the RMST are not applicable. In this article, we consider nonparametric and semiparametric regression methods to estimate the RMST under the setting of length-biased sampling. To assess the covariate effects on the RMST, a semiparametric regression model that directly relates the covariates and the RMST is assumed. Based on the model, we develop unbiased estimating equations to obtain consistent estimators of covariate effects by properly adjusting for informative censoring and length bias. Stochastic process theories are used to establish the asymptotic properties of the proposed estimators. We investigate the finite sample performance through simulations and illustrate the methods by analyzing a prevalent cohort study of dementia in Canada.

Semiparametric regression analysis for alternating recurrent event data.

Alternating recurrent event data arise frequently in clinical and epidemiologic studies, where 2 types of events such as hospital admission and discharge occur alternately over time. The 2 alternating states defined by these recurrent events could each carry important and distinct information about a patient's underlying health condition and/or the quality of care. In this paper, we propose a semiparametric method for evaluating covariate effects on the 2 alternating states jointly. The proposed methodology accounts for the dependence among the alternating states as well as the heterogeneity across patients via a frailty with unspecified distribution. Moreover, the estimation procedure, which is based on smooth estimating equations, not only properly addresses challenges such as induced dependent censoring and intercept sampling bias commonly confronted in serial event gap time data but also is more computationally tractable than the existing rank-based methods. The proposed methods are evaluated by simulation studies and illustrated by analyzing psychiatric contacts from the South Verona Psychiatric Case Register.

Platelet aggregometry cannot identify uremic platelet dysfunction in heart failure patients prior to cardiac surgery.

BACKGROUND: Patients with heart failure often have concomitant renal disease which can result in uremic platelet dysfunction. Determining whether uremia has affected platelets by platelet aggregometry can be challenging in these patients since they are often on antiplatelet medications. This study was undertaken to determine if platelet aggregation studies could identify heart failure patients at risk for uremic bleeding prior to cardiac surgery. METHODS: Platelet aggregation studies from three groups were studied and compared: 17 heart failure patients with mild to moderate renal impairment, 17 heart failure patients without renal abnormalities and 17 healthy volunteers. RESULTS: Platelet aggregation was severely impaired in both heart failure groups with and without renal abnormalities compared to healthy controls, and there were no significant differences in platelet aggregation in response to any of the agonists. There was a pan-decrease in platelet aggregation to all agonists in all heart failure patients. CONCLUSION: Platelet aggregometry does not appear to be useful in measuring platelet dysfunction in heart failure patients with mild to moderate renal impairment.

Nonparametric methods for analyzing recurrent gap time data with application to infections after hematopoietic cell transplant.

Infection is one of the most common complications after hematopoietic cell transplantation. Many patients experience infectious complications repeatedly after transplant. Existing statistical methods for recurrent gap time data typically assume that patients are enrolled due to the occurrence of an event of interest, and subsequently experience recurrent events of the same type; moreover, for one-sample estimation, the gap times between consecutive events are usually assumed to be identically distributed. Applying these methods to analyze the post-transplant infection data will inevitably lead to incorrect inferential results because the time from transplant to the first infection has a different biological meaning than the gap times between consecutive recurrent infections. Some unbiased yet inefficient methods include univariate survival analysis methods based on data from the first infection or bivariate serial event data methods based on the first and second infections. In this article, we propose a nonparametric estimator of the joint distribution of time from transplant to the first infection and the gap times between consecutive infections. The proposed estimator takes into account the potentially different distributions of the two types of gap times and better uses the recurrent infection data. Asymptotic properties of the proposed estimators are established.