Special report of the Massachusetts weight‐of‐evidence workgroup A weight‐of‐evidence approach for evaluating ecological risks

Weight‐of‐evidence is the process by which multiple measurement endpoints are related to an assessment endpoint to evaluate whether significant risk of harm is posed to the environment. In this paper, a methodology is offered for reconciling or balancing multiple lines of evidence pertaining to an assessment endpoint. Weight‐of‐evidence is reflected in three characteristics of measurement endpoints: (a) the weight assigned to each measurement endpoint; (b) the magnitude of response observed in the measurement endpoint; and (c) the concurrence among outcomes of multiple measurement endpoints. First, weights are assigned to measurement endpoints based on attributes related to: (a) strength of association between assessment and measurement endpoints; (b) data quality; and (c) study design and execution. Second, the magnitude of response in the measurement endpoint is evaluated with respect to whether the measurement endpoint indicates the presence or absence of harm; as well as the magnitude. Third, concurrence among measurement endpoints is evaluated by plotting the findings of the two preceding steps on a matrix for each measurement endpoint evaluated. The matrix allows easy visual examination of agreements or divergences among measurement endpoints, facilitating interpretation of the collection of measurement endpoints with respect to the assessment endpoint. A qualitative adaptation of the weight‐of‐evidence approach is also presented.     

Predicting events in clinical trials using two time‐to‐event outcomes

In clinical trials with time‐to‐event outcomes, it is of interest to predict when a prespecified number of events can be reached. Interim analysis is conducted to estimate the underlying survival function. When another correlated time‐to‐event endpoint is available, both outcome variables can be used to improve estimation efficiency. In this paper, we propose to use the convolution of two time‐to‐event variables to estimate the survival function of interest. Propositions and examples are provided based on exponential models that accommodate possible change points. We further propose a new estimation equation about the expected time that exploits the relationship of two endpoints. Simulations and the analysis of real data show that the proposed methods with bivariate information yield significant improvement in prediction over that of the univariate method.     

Less Graft-Versus-Host Disease after Rabbit Antithymocyte Globulin Conditioning in Unrelated Bone Marrow Transplantation for Leukemia and Myelodysplasia: Comparison with Matched Related Bone Marrow Transplantation

One of the major drawbacks for unrelated donor (UD) bone marrow transplantation (BMT) is graft-versus-host disease (GVHD). Despite results from randomized trials, antithymocyte globulin (ATG) is not routinely included for GVHD prophylaxis in UD BMT by many centers. One of ways to demonstrate the usefulness of rabbit ATG in UD BMT is to evaluate how its results approximate to those observed in matched related (MRD) BMT. Therefore, we compared the outcomes between UD BMT with rabbit ATG (Thymoglobulin) for GVHD prophylaxis (n = 25) and MRD BMT (n = 91) for leukemia and myelodysplasia. All but one patient received a myeloablative conditioning regimen. Grades II–IV acute GVHD were similar (39.5% vs. 36%, p = 0.83); however, MRD BMT recipients developed more moderate-severe chronic GVHD (36.5% vs. 8.6%, p = 0.01) and GVHD-related deaths (32.5% vs. 5.6%, p = 0.04). UD BMT independently protected against chronic GVHD (hazard ratio 0.23, p = 0.04). The 6-month transplant-related mortality, 1-year relapse incidence, and 5-year survival rates were similar between patients with non-advanced disease in the MRD and UD BMT groups, 13.8% vs. 16.6% (p = 0.50), 20.8% vs. 16.6% (p = 0.37), and 57% vs. 50% (p = 0.67), respectively. Stable full donor chimerism was equally achieved (71.3% vs. 71.4%, p = 1). Incorporation of rabbit ATG in UD BMT promotes less GVHD, without jeopardizing chimerism evolution, and may attain similar survival outcomes as MRD BMT for leukemia and myelodysplasia especially in patients without advanced disease.     

Bone marrow transplantation: current results in leukemia

Bone marrow transplantation offers two potential therapeutic advantages over more conventional therapy of leukemia. It allows more intensive treatment to be given without regard to marrow toxicity and allows in the case of allogeneic marrow an additional immunotherapeutic effect through graft-versus-host disease (GVHD). Initially, allogeneic transplants in HLA matched sibling donors were only employed in end-stage patients. Although there were encouraging results in terms of long-term therapeutic effects, the overall mortality was prohibitive. Subsequently, patients were transplanted in remission with a marked improvement in overall survival in both acute lymphocytic leukemia and acute non-lymphocytic leukemia. The major obstacles to further improvement in the therapeutic effects of this procedure have been identified (i.e., GVHD, viral infection, and relapse in ALL) and are subject to intensive investigations that already show encouraging results. Syngeneic marrow transplantation is limited for obvious reasons, but early results have shown significant therapeutic effects, in particular, in chronic myelogenous leukemia. These results have encouraged others to use autologous bone marrow. Marrow contamination with unseen tumor cells is being approached by pharmacologic and immunologic techniques designed to "purge" marrow of tumor cells. Animal and initial clinical studies have been encouraging.     

TRAIL-transduced dendritic cells protect mice from acute graft-versus-host disease and leukemia relapse

TRAIL preferentially induces apoptotic cell death in a wide variety of transformed cells, whereas it induces no apoptosis, but inhibits activation of Ag-specific T cells via blockade of cell cycle progression. Although accumulating results suggest that TRAIL is involved in the maintenance of immunological homeostasis under steady state conditions as well as in the initiation and progression of immunopathologies, the potential regulatory effect of TRAIL on immune responses and its therapeutic potential in immunological diseases remains unclear. We report in this study the potential usefulness of TRAIL-transduced dendritic cells (DCs) for the treatment of lethal acute graft-vs-host disease (GVHD) and leukemia relapse. DCs genetically modified to express TRAIL showed potent cytotoxicity against both alloreactive T cells and leukemic cells through the induction of apoptosis. In addition, treatment with genetically modified DCs expressing TRAIL of allogeneic BM transplants recipients with leukemia was effective for protection against acute GVHD and leukemia relapse. Thus, gene transfer of TRAIL to DCs is a novel modality for the treatment of acute GVHD and leukemia relapse by selective targeting of pathogenic T cells and leukemic cells.     

Bayesian approaches to joint cure-rate and longitudinal models with applications to cancer vaccine trials

Complex issues arise when investigating the association between longitudinal immunologic measures and time to an event, such as time to relapse, in cancer vaccine trials. Unlike many clinical trials, we may encounter patients who are cured and no longer susceptible to the time-to-event endpoint. If there are cured patients in the population, there is a plateau in the survival function, S(t), after sufficient follow-up. If we want to determine the association between the longitudinal measure and the time-to-event in the presence of cure, existing methods for jointly modeling longitudinal and survival data would be inappropriate, since they do not account for the plateau in the survival function. The nature of the longitudinal data in cancer vaccine trials is also unique, as many patients may not exhibit an immune response to vaccination at varying time points throughout the trial. We present a new joint model for longitudinal and survival data that accounts both for the possibility that a subject is cured and for the unique nature of the longitudinal data. An example is presented from a cancer vaccine clinical trial.     

Therapeutic effects of hydrogen on chronic graft‐versus‐host disease

The incidence of chronic graft‐versus‐host disease (cGVHD) is rising recent years, which has been the leading cause of non‐transplantation mortality post allogenetic hematopoietic stem cell transplantation (HSCT). Imbalance of inflammatory cytokines and fibrosis plays critical roles in the pathogenesis of cGVHD. Recent studies showed that molecular hydrogen has anti‐inflammatory, antioxidant, anti‐fibrosis effects. Therefore, we hypothesized that molecular hydrogen may have therapeutic effects on cGVHD. To determine whether hydrogen could protect mice from cGVHD in an MHC‐incompatible murine bone marrow transplantation (BMT) model, survival rates of mice were calculated, and skin lesions were also evaluated after BMT. This article demonstrated that administration of hydrogen‐rich saline increased survival rate of cGVHD mice. Administration of hydrogen‐rich saline after transplantation also reduced skin lesions of cGVHD mice. Previously, we reported the therapeutic effects of hydrogen on acute GVHD. However, there was no report on the therapeutic effects of hydrogen on cGVHD mice. It is suggested that hydrogen has a potential as an effective and safe therapeutic agent on cGVHD. This study will provide new ideas on the treatment of cGVHD and has important theoretical values.     

Statistical Analysis of Illness–Death Processes and Semicompeting Risks Data

Summary In many instances, a subject can experience both a nonterminal and terminal event where the terminal event (e.g., death) censors the nonterminal event (e.g., relapse) but not vice versa. Typically, the two events are correlated. This situation has been termed semicompeting risks (e.g., Fine, Jiang, and Chappell, 2001 , Biometrika 88, 907–939; Wang, 2003 , Journal of the Royal Statistical Society, Series B 65, 257–273), and analysis has been based on a joint survival function of two event times over the positive quadrant but with observation restricted to the upper wedge. Implicitly, this approach entertains the idea of latent failure times and leads to discussion of a marginal distribution of the nonterminal event that is not grounded in reality. We argue that, similar to models for competing risks, latent failure times should generally be avoided in modeling such data. We note that semicompeting risks have more classically been described as an illness–death model and this formulation avoids any reference to latent times. We consider an illness–death model with shared frailty, which in its most restrictive form is identical to the semicompeting risks model that has been proposed and analyzed, but that allows for many generalizations and the simple incorporation of covariates. Nonparametric maximum likelihood estimation is used for inference and resulting estimates for the correlation parameter are compared with other proposed approaches. Asymptotic properties, simulations studies, and application to a randomized clinical trial in nasopharyngeal cancer evaluate and illustrate the methods. A simple and fast algorithm is developed for its numerical implementation.     

Successful bone marrow transplantation from an unrelated donor in a child with AML in second remission

In February 1986 we transplanted a 10-year-old girl with AML in second remission with the bone marrow of an unrelated donor. HLA-types were different for one A- and one B-antigen between patient and donor. Conditioning regimen consisted of 14 Gy total body irradiation with lung shielding, 8 X 3 g/m2 cytosin arabinoside and 90 mg/kg cyclophosphamide. GVHD-prophylaxis was performed with cyclosporin A, methotrexate and prednisolone. Only mild GVHD I of the skin could be observed after rapid engraftment. 100 days after transplantation the patient was in good clinical condition and GVHD-prophylaxis was discontinued without any reactivation of acute or chronic GVHD. Engraftment was documented by sex chromosome and blood group typing. 120 days after transplantation leukemic blasts were detected in the peripheral blood and the child died 130 days after BMT from relapse of the leukemia. Despite the negative outcome, this was the first successful bone marrow transplantation from a unrelated donor in Germany.     

Estimating Subject‐Specific Dependent Competing Risk Profile with Censored Event Time Observations

Summary In a longitudinal study, suppose that the primary endpoint is the time to a specific event. This response variable, however, may be censored by an independent censoring variable or by the occurrence of one of several dependent competing events. For each study subject, a set of baseline covariates is collected. The question is how to construct a reliable prediction rule for the future subject's profile of all competing risks of interest at a specific time point for risk‐benefit decision making. In this article, we propose a two‐stage procedure to make inferences about such subject‐specific profiles. For the first step, we use a parametric model to obtain a univariate risk index score system. We then estimate consistently the average competing risks for subjects who have the same parametric index score via a nonparametric function estimation procedure. We illustrate this new proposal with the data from a randomized clinical trial for evaluating the efficacy of a treatment for prostate cancer. The primary endpoint for this study was the time to prostate cancer death, but had two types of dependent competing events, one from cardiovascular death and the other from death of other causes.     

A simple meta-analytic approach for using a binary surrogate endpoint to predict the effect of intervention on true endpoint

A surrogate endpoint is an endpoint that is obtained sooner, at lower cost, or less invasively than the true endpoint for a health outcome and is used to make conclusions about the effect of intervention on the true endpoint. In this approach, each previous trial with surrogate and true endpoints contributes an estimated predicted effect of intervention on true endpoint in the trial of interest based on the surrogate endpoint in the trial of interest. These predicted quantities are combined in a simple random-effects meta-analysis to estimate the predicted effect of intervention on true endpoint in the trial of interest. Validation involves comparing the average prediction error of the aforementioned approach with (i) the average prediction error of a standard meta-analysis using only true endpoints in the other trials and (ii) the average clinically meaningful difference in true endpoints implicit in the trials. Validation is illustrated using data from multiple randomized trials of patients with advanced colorectal cancer in which the surrogate endpoint was tumor response and the true endpoint was median survival time.     

Bone marrow transplantation in childhood leukaemia--experience and strategies in the Federal Republic of Germany

BMT has gained its place in the treatment of childhood leukaemia. Nevertheless, there are still many questions open. In acute lymphoblastic leukaemia children should normally be grafted in 2nd remission (CR). Some high risk cases, however, should probably be grafted in 1st CR. It is not clear whether children with late relapses benefit more from BMT than from renewed chemotherapy. Children with a relapse during maintenance therapy, however, have a better survival rate with BMT. In acute nonlymphoblastic leukaemia certain high risk patients should be grafted in 1st CR but it has still to be shown that BMT is superior to chemotherapy in such cases. It is not clear whether children with a relapse following intensive chemotherapy (such as the BFM-protocols) will benefit from BMT at all. In chronic myelocytic leukaemia, BMT in chronic phase should be performed. Thus, for the first time cure has become possible for this disease. Waiting for acceleration or even the occurrence of a blast crisis decreases the chance of survival after BMT dramatically. Since complications of BMT such as graft-versus-host reaction or severe infections are less frequent in children, relapses remain the main problem after BMT in childhood leukaemia.     

Analysing censored data in agricultural research: A review with examples and software tips

Metric data are usually assessed on a continuous scale with good precision, but sometimes agricultural researchers cannot obtain precise measurements of a variable. Values of such a variable cannot then be expressed as real numbers (e.g., 1.51 or 2.56), but often can be represented by intervals into which the values fall (e.g., from 1 to 2 or from 2 to 3). In this situation, statisticians talk about censoring and censored data, as opposed to missing data, where no information is available at all. Traditionally, in agriculture and biology, three methods have been used to analyse such data: (a) when intervals are narrow, some form of imputation (e.g., mid‐point imputation) is used to replace the interval and traditional methods for continuous data are employed (such as analyses of variance [ANOVA] and regression); (b) for time‐to‐event data, the cumulative proportions of individuals that experienced the event of interest are analysed, instead of the individual observed times‐to‐event; (c) when intervals are wide and many individuals are collected, non‐parametric methods of data analysis are favoured, where counts are considered instead of the individual observed value for each sample element. In this paper, we show that these methods may be suboptimal: The first one does not respect the process of data collection, the second leads to unreliable standard errors (SEs), while the third does not make full use of all the available information. As an alternative, methods of survival analysis for censored data can be useful, leading to reliable inferences and sound hypotheses testing. These methods are illustrated using three examples from plant and crop sciences.     

The evaluation of multiple surrogate endpoints

Surrogate endpoints are desirable because they typically result in smaller, faster efficacy studies compared with the ones using the clinical endpoints. Research on surrogate endpoints has received substantial attention lately, but most investigations have focused on the validity of using a single biomarker as a surrogate. Our paper studies whether the use of multiple markers can improve inferences about a treatment's effects on a clinical endpoint. We propose a joint model for a time to clinical event and for repeated measures over time on multiple biomarkers that are potential surrogates. This model extends the formulation of Xu and Zeger (2001, in press) and Fawcett and Thomas (1996, Statistics in Medicine 15, 1663-1685). We propose two complementary measures of the relative benefit of multiple surrogates as opposed to a single one. Markov chain Monte Carlo is implemented to estimate model parameters. The methodology is illustrated with an analysis of data from a schizophrenia clinical trial.     

Using expert knowledge to incorporate uncertainty in cause‐of‐death assignments for modeling of cause‐specific mortality

Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause‐specific mortality provide an example of implicit use of expert knowledge when causes‐of‐death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause‐specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause‐of‐death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event‐time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause‐of‐death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause‐of‐death assignment in modeling of cause‐specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause‐specific survival data for white‐tailed deer, and compared results. We demonstrate that model selection results changed between the two approaches, and incorporating observer knowledge in cause‐of‐death increased the variability associated with parameter estimates when compared to the traditional approach. These differences between the two approaches can impact reported results, and therefore, it is critical to explicitly incorporate expert knowledge in statistical methods to ensure rigorous inference.     

Allogeneic bone marrow transplantation for leukaemia and aplastic anaemia. Results of the Leipzig BMT Group

In acute leukaemias there was a stable plateau in the survival curve at 45% after two years if grafted in first complete remission (n = 20) but only 13% of the patients are disease-free alive if grafted in a more advanced stage of the disease (n = 8). In 16 patients transplanted for chronic myeloid leukaemia the overall survival is 40%, in cases with graft-versus-host disease (GVHD) prevention by cyclosporine survival rate could be improved. Only 8 patients with severe aplastic anaemia, partially in low performance status were able to be transplanted; three died of infections, another by acute GVHD. The fatal complications in our study characterize the international well-known major problems in BMT: GVHD, interstitial pneumonitis, infections, graft failure in aplastic anaemia and recurrence of leukaemia, especially in more advanced leukaemia stage.     

Testing for Treatment Effects on Subsets of Endpoints

Multiple endpoints are tested to assess an overall treatment effect and also to identify which endpoints or subsets of endpoints contributed to treatment differences. The conventional p‐value adjustment methods, such as single‐step, step‐up, or step‐down procedures, sequentially identify each significant individual endpoint. Closed test procedures can also detect individual endpoints that have effects via a step‐by‐step closed strategy. This paper proposes a global‐based statistic for testing an a priori number, say, r of the k endpoints, as opposed to the conventional approach of testing one (r = 1) endpoint. The proposed test statistic is an extension of the single‐step p‐value‐based statistic based on the distribution of the smallest p‐value. The test maintains strong control of the FamilyWise Error (FWE) rate under the null hypothesis of no difference in any (sub)set of r endpoints among all possible combinations of the k endpoints. After rejecting the null hypothesis, the individual endpoints in the sets that are rejected can be tested further, using a univariate test statistic in a second step, if desired. However, the second step test only weakly controls the FWE. The proposed method is illustrated by application to a psychosis data set.     

Clinical and immunopathological significance of chimerism in bone marrow and organ transplantations

Chimerism is an exceptional immunogenetic state, characterized by the survival and collaboration of cell populations originated from two different individuals. The prerequisites to induce chimerism are immunosuppression, myeloablation or severe immunodeficiency of the recipients on one side and donor originated immuno-hematopoietic cells in the graft on the other. Special immunogenetic conditions to establish chimerism are combined with bone marrow transplantation, transfusion and various kinds of solid organ grafting. There are various methods to detect the type of chimera state depending on the immunogenetic differences between the donor and recipient. The chimera state seems to be one of the leading factors to influence the course of the post-transplant period, the frequency and severity of graft-versus-host disease (GVHD), and the rate of relapse. However, the most important contribution of the chimeric state is the development of graft versus leukemia (GVL) effect. A new conditioning protocol (DBM/Ara-C/Cy) for allogeneic BMT in CML patients and its consequence on chimera state and GVL effect is demonstrated.     

Sample size determination in clinical trials with multiple co‐primary endpoints including mixed continuous and binary variables

In the field of pharmaceutical drug development, there have been extensive discussions on the establishment of statistically significant results that demonstrate the efficacy of a new treatment with multiple co‐primary endpoints. When designing a clinical trial with such multiple co‐primary endpoints, it is critical to determine the appropriate sample size for indicating the statistical significance of all the co‐primary endpoints with preserving the desired overall power because the type II error rate increases with the number of co‐primary endpoints. We consider overall power functions and sample size determinations with multiple co‐primary endpoints that consist of mixed continuous and binary variables, and provide numerical examples to illustrate the behavior of the overall power functions and sample sizes. In formulating the problem, we assume that response variables follow a multivariate normal distribution, where binary variables are observed in a dichotomized normal distribution with a certain point of dichotomy. Numerical examples show that the sample size decreases as the correlation increases when the individual powers of each endpoint are approximately and mutually equal.     

Acute Graft-Versus-Host Disease of the Kidney in Allogeneic Rat Bone Marrow Transplantation

Allogeneic hematopoietic cell or bone marrow transplantation (BMT) causes graft-versus-host-disease (GVHD). However, the involvement of the kidney in acute GVHD is not well-understood. Acute GVHD was induced in Lewis rats (RT1^l) by transplantation of Dark Agouti (DA) rat (RT1^a) bone marrow cells (6.0×10⁷ cells) without immunosuppression after lethal irradiation (10 Gy). We examined the impact of acute GVHD on the kidney in allogeneic BMT rats and compared them with those in Lewis-to-Lewis syngeneic BMT control and non-BMT control rats. In syngeneic BMT and non-BMT control rats, acute GVHD did not develop by day 28. In allogeneic BMT rats, severe acute GVHD developed at 21–28 days after BMT in the skin, intestine, and liver with decreased body weight (>20%), skin rush, diarrhea, and liver dysfunction. In the kidney, infiltration of donor-type leukocytes was by day 28. Mild inflammation characterized by infiltration of CD3+ T-cells, including CD8+ T-cells and CD4+ T-cells, and CD68+ macrophages to the interstitium around the small arteries was noted. During moderate to severe inflammation, these infiltrating cells expanded into the peritubular interstitium with peritubular capillaritis, tubulitis, acute glomerulitis, and endarteritis. Renal dysfunction also developed, and the serum blood urea nitrogen (33.9±4.7 mg/dL) and urinary N-acetyl-β-D-glucosaminidase (NAG: 31.5±15.5 U/L) levels increased. No immunoglobulin and complement deposition was detected in the kidney. In conclusion, the kidney was a primary target organ of acute GVHD after BMT. Acute GVHD of the kidney was characterized by increased levels of urinary NAG and cell-mediated injury to the renal microvasculature and renal tubules.