Surgical evidence-based comparison of [68Ga]Ga-FAPI-04 PET and MRI-DWI for assisting debulking surgery in ovarian cancer patients.

PURPOSE: Imaging assessment of abdominopelvic tumor burden is crucial for debulking surgery decision in ovarian cancer patients. This study aims to compare the efficiency of [68Ga]Ga-FAPI-04 FAPI PET and MRI-DWI in the preoperative evaluation and its potential impact to debulking surgery decision. METHODS: Thirty-six patients with suspected/confirmed ovarian cancer were enrolled and underwent integrated [68Ga]Ga-FAPI-04 PET/MRI. Nineteen patients (15 stage III-IV and 4 I-II stage) who underwent debulking surgery were involved in the diagnostic efficiency analysis. The images of [68Ga]Ga-FAPI-04 PET and MRI-DWI were visually analyzed respectively. Immunohistochemistry on FAP was performed in metastatic lesions to investigate the radiological missing of [68Ga]Ga-FAPI-04 PET as well as its different performance in primary debulking surgery (PDS) and interval debulking surgery (IDS) patients. Potential imaging impact on management was also studied in 35 confirmed ovarian cancer patients. RESULTS: [68Ga]Ga-FAPI-04 PET displayed higher sensitivity (76.8% vs.59.9%), higher accuracy (84.9% vs. 80.7%), and lower missing rate (23.2% vs. 40.1%) than MRI-DWI in detecting abdominopelvic metastasis. The diagnostic superiority of [68Ga]Ga-FAPI-04 PET is more obvious in PDS patients but diminished in IDS patients. [68Ga]Ga-FAPI-04 PET outperformed MRI-DWI in 70.8% abdominopelvic regions (17/24), which contained seven key regions that impact the resectability and surgical complexity. MRI-DWI hold advantage in the peritoneal surface of the bladder and the central tendon of the diaphragm. Of the contradictory judgments between the two modalities (14.9%), [68Ga]Ga-FAPI-04 PET correctly identified more lesions, particularly in PDS patients (73.8%). In addition, FAP expression was independent of lesion size and decreased in IDS patients. [68Ga]Ga-FAPI-04 PET changed 42% of surgical planning that was previously based on MRI-DWI. CONCLUSION: [68Ga]Ga-FAPI-04 PET is more efficient in assisting debulking surgery in ovarian cancer patients than MRI-DWI. Integrated [68Ga]Ga-FAPI-04 PET/MR imaging is a potential method for planning debulking surgery in ovarian cancer patients.

Analysis of clinical diagnosis and treatment of intestinal volvulus.

BACKGROUND: The aim of this study is to investigate the clinical characteristics and treatment experience of intestinal volvulus, and to analyze the incidence of adverse events and related risk factors of intestinal volvulus. METHODS: Thirty patients with intestinal volvulus admitted to the Digestive Emergency Department of Xijing Hospital from January 2015 to December 2020 were selected. The clinical manifestations, laboratory tests, treatment and prognosis were retrospectively analyzed. RESULTS: A total of 30 patients with volvulus were enrolled in this study, including 23 males (76.7%), with a median age of 52 years (33-66 years). The main clinical manifestations were abdominal pain in 30 cases (100%), nausea and vomiting in 20 cases (67.7%), cessation of exhaust and defecation in 24 cases (80%), and fever in 11 cases (36.7%). The positions of intestinal volvulus were jejunum in 11 cases (36.7%), ileum and ileocecal in 10 cases (33.3%), sigmoid colon in 9 cases (30%). All 30 patients received surgical treatment. Among the 30 patients underwent surgery, 11 patients developed intestinal necrosis. We found that the longer the disease duration (> 24 h), the higher the incidence of intestinal necrosis, and the higher the incidence of ascites, white blood cell count and neutrophil ratio in the intestinal necrosis group were significantly higher than those in the non-intestinal necrosis group (p < 0.05). After treatment, 1 patient died of septic shock after operation, and 2 patients with recurrent volvulus were followed up within 1 year. The overall cure rate was 90%, the mortality rate was 3.3%, and the recurrence rate was 6.6%. CONCLUSION: Laboratory examination, abdominal CT and dual-source CT are very important for the diagnosis of volvulus in patients with abdominal pain as the main symptom. Increased white blood cell count, neutrophil ratio, ascites and long course of disease are important for predicting intestinal volvulus accompanied by intestinal necrosis. Early diagnosis and timely intervention can save lives and prevent serious complications.

JASPER: Phase 2 trial of first-line niraparib plus pembrolizumab in patients with advanced non-small cell lung cancer.

BACKGROUND: Poly(ADP-ribose) polymerase (PARP) inhibitors may synergize with programmed cell death receptor-1 (PD-1) inhibitors to enhance adaptive and innate antitumor immune responses. In the phase 2 JASPER study (NCT04475939), the PARP inhibitor niraparib was evaluated in combination with the PD-1 inhibitor pembrolizumab in patients with metastatic and/or locally advanced non-small cell lung cancer (NSCLC). METHODS: Patients whose tumors had programmed cell death ligand 1 (PD-L1) tumor proportion scores (TPS) ≥50% (cohort 1) or 1%-49% (cohort 2) received first-line niraparib (200 mg once daily) plus pembrolizumab (200 mg every 3 weeks). The primary end point was investigator-assessed objective response rate (ORR). Secondary end points included duration of response (DoR), progression-free survival (PFS), overall survival (OS), safety, and pharmacokinetics. RESULTS: Thirty-eight patients were enrolled in cohorts 1 and 2. In cohort 1, ORR (95% confidence interval [CI]) was 56.3% (9 of 16 patients; 29.9%-80.2%); 2 of 16 patients had complete responses and 7 of 16 had partial responses (PRs). In cohort 2, ORR was 20.0% (5.7%-43.7%) with 4 of 20 PRs. In cohorts 1 and 2, the median DoR was 19.7 months (95% CI, 4.2 months to not estimable [NE]) and 9.4 months (95% CI, 4.2 months to NE), the median PFS was 8.4 months (95% CI, 3.9-22.1 months) and 4.2 months (95% CI, 2.0-6.2 months), and the median OS was NE (95% CI, 6.0 months to NE) and 7.7 months (95% CI, 4.0-12.5 months), respectively. Grade ≥3 treatment-emergent adverse events occurred in 88.2% and 85.7% of patients in cohorts 1 and 2, respectively. Safety was consistent with known profiles of single-agent niraparib and pembrolizumab. CONCLUSIONS: Niraparib plus pembrolizumab showed clinical activity in patients with advanced and/or metastatic NSCLC. LAY SUMMARY: The JASPER clinical trial studied a new combination treatment for advanced or metastatic non-small cell lung cancer (NSCLC). Pembrolizumab, a drug approved for NSCLC, was given with niraparib. Previous research showed that these 2 drugs together might work better than either drug alone. This study found that more than half of patients with high levels of a tumor marker responded to the combination, and one-fifth of patients with lower levels of the marker responded. The types of side effects from the combination were similar to side effects from both drugs alone. These results support more research on this combination.

MOVER confidence intervals for a difference or ratio effect parameter under stratified sampling.

Stratification is commonly employed in clinical trials to reduce the chance covariate imbalances and increase the precision of the treatment effect estimate. We propose a general framework for constructing the confidence interval (CI) for a difference or ratio effect parameter under stratified sampling by the method of variance estimates recovery (MOVER). We consider the additive variance and additive CI approaches for the difference, in which either the CI for the weighted difference, or the CI for the weighted effect in each group, or the variance for the weighted difference is calculated as the weighted sum of the corresponding stratum-specific statistics. The CI for the ratio is derived by the Fieller and log-ratio methods. The weights can be random quantities under the assumption of a constant effect across strata, but this assumption is not needed for fixed weights. These methods can be easily applied to different endpoints in that they require only the point estimate, CI, and variance estimate for the measure of interest in each group across strata. The methods are illustrated with two real examples. In one example, we derive the MOVER CIs for the risk difference and risk ratio for binary outcomes. In the other example, we compare the restricted mean survival time and milestone survival in stratified analysis of time-to-event outcomes. Simulations show that the proposed MOVER CIs generally outperform the standard large sample CIs, and that the additive CI approach performs better than the additive variance approach. Sample SAS code is provided in the Supplementary Material.

Complex survival trial design by the product integration method.

Nonproportional hazards (NPHs) are often observed in survival trials such as the immunotherapy cancer trials. Under NPH, the classical log-rank test can be inefficient, and the estimated hazards ratio from the Cox model is difficult to interpret. The weighted log-rank test, and the tests for comparing the restricted mean survival time or the milestone survival become increasingly popular in handling NPH. The sample size calculation for these tests may require high-dimensional numerical integration. We present a sample size determination method for survival trials via product integration on the basis of a continuous-time multistate Markov model. The main challenge of the method lies in the design of the multistate model under a complex NPH pattern, and this is illustrated for NPH induced by delayed effect with individual heterogeneity in the lag duration, cure fractions, and treatment switching due to disease progression or noncompliance. Numerical examples are presented to demonstrate the accuracy of the proposed method. We obtain the following findings. The powers of the tests for milestone survival and RMST depend on both the trial duration and milestone timepoint, and may not increase as the milestone timepoint increases. If the milestone timepoint is appropriately chosen, the RMST test can be more powerful than the conventional log-rank test in the presence of diminishing treatment effect or in the proportional hazards cure model. In general, the RMST test yields lower power than a proper Fleming-Harrington weighted log-rank test.

Clinicopathologic and molecular features of denosumab-treated giant cell tumour of bone (GCTB): Analysis of 21 cases.

GCTB is an osteolytic, locally-aggressive, rarely-metastasizing tumour, characterized by abundance of osteoclast-like giant cells, induced by neoplastic mononuclear cells expressing high-levels of the receptor activator of nuclear factor Kappa-B ligand (RANKL), a mediator of osteoclast activation. Although the mainstay of treatment is complete tumour removal with preservation of bone, therapy with denosumab, an inhibitor of RANKL, has been introduced for selected cases. OBJECTIVES: Denosumab-treated GCTB (DT-GCTB) was reported to show a wide spectrum of histological changes such as depletion of osteoclast-like giant cells and intralesional bone deposition, which may lead to diagnostic difficulties. We investigated clinicopathologic and molecular features of DT-GCTB, matched with pre-therapy samples. PARTICIPANTS: 21 cases were included (13 females, 8 males), aged 15 to 64 (median, 30 years). RESULTS: DT-GCTB showed development of sclerotic neocortex and varying degrees of osteosclerosis radiographically. Marked depletion of giant cells, different degree of ossification, fibrosis, and proliferation of mononuclear cells was observed. Staining for H3.3G34W was positive in mononuclear cells in 19 cases (90.5%), while one negative case was positive for H3.3G34V. H3F3A G34W mutation was confirmed in 17 of 19 cases (89.5%), corresponding to nuclear staining with H3.3 G34W antibody. G34L mutation was detected in one G34W negative case, in which H3.3 G34V nuclear positive staining was observed, possibly due to cross-reaction. CONCLUSIONS: Post-therapy tumours still exhibit a similar mutation profile, while significantly differing from classic GCTB morphologically. Correlation with history of denosumab administration, awareness of features of DT-GCTB, IHC and molecular studies for histone H3 mutations are important in its assessment.

Sample size calculation for recurrent event data with additive rates models.

This paper discusses the design of clinical trials where the primary endpoint is a recurrent event with the focus on the sample size calculation. For the problem, a few methods have been proposed but most of them assume a multiplicative treatment effect on the rate or mean number of recurrent events. In practice, sometimes the additive treatment effect may be preferred or more appealing because of its intuitive clinical meaning and straightforward interpretation compared to a multiplicative relationship. In this paper, new methods are presented and investigated for the sample size calculation based on the additive rates model for superiority, non-inferiority, and equivalence trials. They allow for flexible baseline rate function, staggered entry, random dropout, and overdispersion in event numbers, and simulation studies show that the proposed methods perform well in a variety of settings. We also illustrate how to use the proposed methods to design a clinical trial based on real data.

Some new confidence intervals for Kaplan-Meier based estimators from one and two sample survival data.

The restricted mean survival time (RMST) has been popularly used to assess the treatment effect in survival trials. Greenwood's formula is often used to estimate the variance of RMST, and the resulting Wald confidence interval (CI) tends to be liberal in small and moderate samples. We propose the empirical likelihood ratio, score-type, and loglog transformed CIs for RMST in a single sample. The method of variance estimates recovery technique is used to derive the CIs for the difference and ratio parameters in the two sample inference. A variance estimate, which assumes equal survival curves, but possibly different censoring rates in the two groups, is proposed for comparing two groups. The new variance estimate shows excellent performance in testing for superiority, and also works well for a noninferiority test with a small margin, and for the interval estimation when the two survival curves are close. We use similar techniques to construct CIs for comparing two milestone survival probabilities. Numerical examples are used to assess these interval estimation methods.

Power and sample size for GEE analysis of incomplete paired outcomes in 2 × 2 crossover trials.

The 2 × 2 crossover trial uses subjects as their own control to reduce the intersubject variability in the treatment comparison, and typically requires fewer subjects than a parallel design. The generalized estimating equations (GEE) methodology has been commonly used to analyze incomplete discrete outcomes from crossover trials. We propose a unified approach to the power and sample size determination for the Wald Z-test and t-test from GEE analysis of paired binary, ordinal and count outcomes in crossover trials. The proposed method allows misspecification of the variance and correlation of the outcomes, missing outcomes, and adjustment for the period effect. We demonstrate that misspecification of the working variance and correlation functions leads to no or minimal efficiency loss in GEE analysis of paired outcomes. In general, GEE requires the assumption of missing completely at random. For bivariate binary outcomes, we show by simulation that the GEE estimate is asymptotically unbiased or only minimally biased, and the proposed sample size method is suitable under missing at random (MAR) if the working correlation is correctly specified. The performance of the proposed method is illustrated with several numerical examples. Adaption of the method to other paired outcomes is discussed.

Score confidence intervals and sample sizes for stratified comparisons of binomial proportions.

In a series of articles, Gart and Nam construct the efficient score tests and confidence intervals with or without skewness correction for stratified comparisons of binomial proportions on the risk difference, relative risk, and odds ratio effect metrics. However, the stratified score methods and their properties are not well understood. We rederive the efficient score tests, which reveals their theoretical relationship with the contrast-based score tests, and provides a basis for adapting the method by using other weighting schemes. The inverse variance weight is optimal for a common treatment effect in large samples. We explore the behavior of the score approach in the presence of extreme outcomes when either no or all subjects in some strata are responders, and provide guidance on the choice of weights in the analysis of rare events. The score method is recommended for studies with a small number of moderate or large sized strata. A general framework is proposed to calculate the asymptotic power and sample size for the score test in superiority, noninferiority and equivalence clinical trials, or case-control studies. We also describe a nearly exact procedure that underestimates the exact power, but the degree of underestimation can be controlled to a negligible level. The proposed methods are illustrated by numerical examples.

Grade 3 Pancreatic Neuroendocrine Tumors on MDCT: Establishing a Diagnostic Model and Comparing Survival Against Pancreatic Ductal Adenocarcinoma.

OBJECTIVE. The purpose of this study is to establish a diagnostic model for differentiating grade 3 (G3) pancreatic neuroendocrine tumors (PNETs) from pancreatic ductal adenocarcinomas (PDACs) and to analyze survival outcomes. MATERIALS AND METHODS. Twenty patients with G3 PNETs and 58 patients with PDACs confirmed by surgery or biopsy were retrospectively included. Demographic and radiologic information was collected. Univariate analyses and binary logistic regression analyses were performed to identify independent factors and establish a diagnostic model. An ROC curve was created to determine diagnostic ability. Kaplan-Meier survival analysis was performed. RESULTS. Patients with G3 PNETs were more likely to present with normal carbohydrate antigen (CA) 19-9 levels, normal pancreatic ducts, and round tumors with well-defined margins and higher portal enhancement ratios than were patients with PDAC (p < 0.05). After multivariate analysis, a normal CA 19-9 level (odds ratio, 0.0125; 95% CI, 0.0008-0.2036), round tumor shape (odds ratio, 0.0143; 95% CI, 0.0004-0.5461), and pancreatic duct dilation of 4 mm or less (odds ratio, 17.9804; 95% CI, 1.0098-320.1711) were independent predictors of G3 PNETs. The AUC of the ROC curve was 0.916, and sensitivity and specificity were 90.0% and 81.0%, respectively. Furthermore, patients with G3 PNETs had better overall survival than patients with PDACs. Among patients in the G3 PNET subgroup, patients with liver or lymph node metastases had worse overall survival than patients without metastases. CONCLUSION. A diagnostic model was established to differentiate G3 PNETs from PDACs. A normal CA 19-9 level, round tumor shape, and pancreatic duct dilation of 4 mm or less were factors that were strongly predictive of G3 PNET.

[EFFICACY, PHARMACOKINETICS, PHARMACODYNAMICS, AND SAFETY OF INTRAVENOUS C1 INHIBITOR FOR LONG-TERM PROPHYLAXIS AND TREATMENT OF BREAKTHROUGH ATTACKS IN JAPANESE SUBJECTS WITH HEREDITARY ANGIOEDEMA: A PHASE 3 OPEN-LABEL STUDY].

BACKGROUND: Hereditary angioedema (HAE) is associated with recurrent, painful, and potentially lifethreatening attacks characterized by swelling of subcutaneous or submucosal tissues. PURPOSE: To investigate the efficacy, safety, pharmacokinetics, and pharmacodynamics of repeat-use C1 inhibitor (C1-INH) replacement therapy for long-term prophylaxis and treatment of breakthrough attacks in the management of Japanese patients with HAE type I or II. METHODS: An open-label, single-arm, Phase 3 study was conducted in Japanese patients with HAE (NCT02865720). For patients 6 years of age or older, 1000U were administered biweekly (by a healthcare professional or self-administered) via intravenous infusion. RESULTS: In 8 enrolled patients, the mean number of attacks normalized per month was lower during C1-INH treatment than during the 3 months prior (1.826 vs. 3.375). Clinically meaningful mean change from baseline in the angioedema-quality of life (AE-QoL) total score was shown during treatment with C1-INH. Pharmacokinetic data showed markedly higher and enduring post-baseline plasma levels of C1-INH functional activity and C1-INH antigen concentration, starting from 0.5h after first dose of C1-INH and lasting up to 72 hours. C1-INH was well tolerated with no new safety signals identified in this population of Japanese patients with HAE. CONCLUSION: C1-INH was effective for long-term prophylaxis and treatment of breakthrough attacks with favourable safety profile in Japanese patients with HAE.

A randomized trial of human C1 inhibitor prophylaxis in children with hereditary angioedema.

BACKGROUND: Patients with hereditary angioedema with C1 inhibitor deficiency or dysfunction have burdensome recurrent angioedema attacks. The safety, efficacy, and health-related quality of life (HRQoL) outcomes of C1 inhibitor (C1-INH) prophylaxis (intravenously administered) in patients aged 6-11 years were investigated. METHODS: Eligible patients were enrolled in a randomized, single-blind, crossover, phase 3 trial. After a 12-week baseline observation period (BOP), patients received 500 or 1000 U C1-INH, twice weekly, for 12 weeks before crossing over to the alternate dose for 12 weeks. The primary efficacy end-point was the monthly normalized number of angioedema attacks (NNA). HRQoL was assessed using the EuroQoL 5-dimensional descriptive system youth version and visual analog scale (EQ-VAS). RESULTS: Twelve randomized patients had a median (range) age of 10.0 (7-11) years. Mean (SD) percentage reduction in monthly NNA from BOP was 71.1% (27.1%) with 500 U and 84.5% (20.0%) with 1000 U C1-INH. Mean (SD) within-patient difference (-0.4 [0.58]) for monthly NNA with both doses was significant (P = 0.035 [90% CI, -0.706 to -0.102]). Cumulative attack severity, cumulative daily severity, and number of acute attacks treated were reduced. No serious adverse events or discontinuations occurred. Mean EQ-VAS change from BOP to week 9 of treatment (500 U C1-INH, 10.4; 1000 U C1-INH, 21.6) was greater than the minimal important difference, indicating a meaningful HRQoL change. CONCLUSIONS: C1-INH prophylaxis was effective, safe, and well tolerated in children aged 6-11 years experiencing recurrent angioedema attacks. A post hoc analysis indicated a meaningful improvement in HRQoL with C1-INH. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT02052141.

A monotone data augmentation algorithm for multivariate nonnormal data: With applications to controlled imputations for longitudinal trials.

An efficient monotone data augmentation (MDA) algorithm is proposed for missing data imputation for incomplete multivariate nonnormal data that may contain variables of different types and are modeled by a sequence of regression models including the linear, binary logistic, multinomial logistic, proportional odds, Poisson, negative binomial, skew-normal, skew-t regressions, or a mixture of these models. The MDA algorithm is applied to the sensitivity analyses of longitudinal trials with nonignorable dropout using the controlled pattern imputations that assume the treatment effect reduces or disappears after subjects in the experimental arm discontinue the treatment. We also describe a heuristic approach to implement the controlled imputation, in which the fully conditional specification method is used to impute the intermediate missing data to create a monotone missing pattern, and the missing data after dropout are then imputed according to the assumed nonignorable mechanisms. The proposed methods are illustrated by simulation and real data analyses. Sample SAS code for the analyses is provided in the supporting information.

Sample size calculation for the Andersen-Gill model comparing rates of recurrent events.

Recurrent events arise frequently in biomedical research, where the subject may experience the same type of events more than once. The Andersen-Gill (AG) model has become increasingly popular in the analysis of recurrent events particularly when the event rate is not constant over time. We propose a procedure for calculating the power and sample size for the robust Wald test from the AG model in superiority, noninferiority, and equivalence clinical trials. Its performance is demonstrated by numerical examples. Sample SAS code is provided in the Supplementary Material.

Controlled pattern imputation for sensitivity analysis of longitudinal binary and ordinal outcomes with nonignorable dropout.

The controlled imputation method refers to a class of pattern mixture models that have been commonly used as sensitivity analyses of longitudinal clinical trials with nonignorable dropout in recent years. These pattern mixture models assume that participants in the experimental arm after dropout have similar response profiles to the control participants or have worse outcomes than otherwise similar participants who remain on the experimental treatment. In spite of its popularity, the controlled imputation has not been formally developed for longitudinal binary and ordinal outcomes partially due to the lack of a natural multivariate distribution for such endpoints. In this paper, we propose 2 approaches for implementing the controlled imputation for binary and ordinal data based respectively on the sequential logistic regression and the multivariate probit model. Efficient Markov chain Monte Carlo algorithms are developed for missing data imputation by using the monotone data augmentation technique for the sequential logistic regression and a parameter-expanded monotone data augmentation scheme for the multivariate probit model. We assess the performance of the proposed procedures by simulation and the analysis of a schizophrenia clinical trial and compare them with the fully conditional specification, last observation carried forward, and baseline observation carried forward imputation methods.

A noniterative sample size procedure for tests based on t distributions.

A noniterative sample size procedure is proposed for a general hypothesis test based on the t distribution by modifying and extending Guenther's approach for the one sample and two sample t tests. The generalized procedure is employed to determine the sample size for treatment comparisons using the analysis of covariance (ANCOVA) and the mixed effects model for repeated measures in randomized clinical trials. The sample size is calculated by adding a few simple correction terms to the sample size from the normal approximation to account for the nonnormality of the t statistic and lower order variance terms, which are functions of the covariates in the model. But it does not require specifying the covariate distribution. The noniterative procedure is suitable for superiority tests, noninferiority tests, and a special case of the tests for equivalence or bioequivalence and generally yields the exact or nearly exact sample size estimate after rounding to an integer. The method for calculating the exact power of the two sample t test with unequal variance in superiority trials is extended to equivalence trials. We also derive accurate power formulae for ANCOVA and mixed effects model for repeated measures, and the formula for ANCOVA is exact for normally distributed covariates. Numerical examples demonstrate the accuracy of the proposed methods particularly in small samples.

Sample size for comparing negative binomial rates in noninferiority and equivalence trials with unequal follow-up times.

We derive the sample size formulae for comparing two negative binomial rates based on both the relative and absolute rate difference metrics in noninferiority and equivalence trials with unequal follow-up times, and establish an approximate relationship between the sample sizes required for the treatment comparison based on the two treatment effect metrics. The proposed method allows the dispersion parameter to vary by treatment groups. The accuracy of these methods is assessed by simulations. It is demonstrated that ignoring the between-subject variation in the follow-up time by setting the follow-up time for all individuals to be the mean follow-up time may greatly underestimate the required size, resulting in underpowered studies. Methods are provided for back-calculating the dispersion parameter based on the published summary results.

Algorithms for imputing partially observed recurrent events with applications to multiple imputation in pattern mixture models.

Five algorithms are described for imputing partially observed recurrent events modeled by a negative binomial process, or more generally by a mixed Poisson process when the mean function for the recurrent events is continuous over time. We also discuss how to perform the imputation when the mean function of the event process has jump discontinuities. The validity of these algorithms is assessed by simulations. These imputation algorithms are potentially very useful in the implementation of pattern mixture models, which have been popularly used as sensitivity analysis under the non-ignorability assumption in clinical trials. A chronic granulomatous disease trial is analyzed for illustrative purposes.