Survival analysis encompasses investigation of time to event data. In most clinical studies, estimating the cumulative incidence function (or the probability of experiencing an event by a given time) is of primary interest. When the data consist of patients who experience an event and censored individuals, a nonparametric estimate of the cumulative incidence can be obtained using the Kaplan -Meier method. Under this approach, the censoring mechanism is assumed to be noninformative. In other words, the survival time of an individual (or the time at which a subject experiences an event) is assumed to be independent of a mechanism that would cause the patient to be censored. Often times, a patient may experience an event other than the one of interest which alters the probability of experiencing the event of interest. Such events are known as competing risk events. In this setting, it would often be of interest to calculate the cumulative incidence of a specific event of interest. Any subject who does not experience the event of interest can be treated as censored. However, a patient experiencing a competing risk event is censored in an informative manner. Hence, the Kaplan -Meier estimation procedure may not be directly applicable. The cumulative incidence function for an event of interest must be calculated by appropriately accounting for the presence of competing risk events. In this paper, we illustrate nonparametric estimation of the cumulative incidence function for an event of interest in the presence of competing risk events using two published data sets. We compare the resulting estimates with those obtained using the Kaplan -Meier approach to demonstrate the importance of appropriately estimating the cumulative incidence of an event of interest in the presence of competing risk events. Survival analysis is the analysis of data measured from a specific time of origin until an event of interest or a specified endpoint (Collett, 1994). For example, in order to determine the incidence of death due to breast cancer among breast cancer patients, every patient will be followed from a baseline date (such as date of diagnosis or date of surgery) until the date of death due to breast cancer or study closing date. A patient who dies of breast cancer during the study period would be considered to have an 'event' at their date of death. A patient who is alive at the end of the study would be considered to be 'censored'. Thus, every patient provides two pieces of information: follow-up time and status (i.e., event or censored). However, a patient can experience an event different from the event of interest. For example, a breast cancer patient may die due to causes unrelated to the disease. Such events are termed competing risk events. Survival data are often summarised using the cumulative incidence function for an event. The goal of this paper is to illustrate to the clinical investigator the nonparametric estimation of the cumulative incidence for an event of interest in the presence of competing risk events. GENERA...

Over the past decade, the use of parenchymal-sparing segmental resections has increased significantly. The number of hepatic segments resected and operative blood loss were the only predictors of both perioperative morbidity and mortality, and reductions in both are largely responsible for the decrease in perioperative mortality, which has occurred despite an increase in concomitant major procedures.

Age and performance status were the only variables identified on standard multivariate analysis. Cut point analysis of age determined that patients age < or = 50 years had significantly improved outcome compared with older patients. RPA of 282 patients identified three distinct prognostic classes: class 1 (patients < 50 years), class 2 (patients > or =50; Karnofsky performance score [KPS] > or = 70) and class 3 (patients > or = 50; KPS < 70). These three classes significantly distinguished outcome with regard to both overall and failure-free survival. Analysis of the RTOG data set confirmed the validity of this classification. CONCLUSION The MSKCC prognostic score is a simple, statistically powerful model with universal applicability to patients with newly diagnosed PCNSL. We recommend that it be adopted for the management of newly diagnosed patients and incorporated into the design of prospective clinical trials.

Perioperative blood transfusion is a risk factor for poor outcome after liver resection. Blood conservation methods should be used to avoid transfusion, especially in patents currently requiring limited amounts of transfused blood products.

Sun exposure is associated with increased survival from melanoma.

Our data suggest that individuals in whom gefitinib is efficacious are more likely to have adenocarcinomas of the bronchioloalveolar subtype and to be never smokers. These observations may provide clues to mechanisms determining sensitivity to this agent and suggest that NSCLC has a different biology in patients who never smoked and those with bronchioloalveolar carcinoma.

Jaundice is common (34%) in patients who present with gallbladder cancer and is an indicator of advanced malignancy. These data do not support routine operative exploration of patients with jaundice secondary to gallbladder cancer.

The Cancer Vaccine Consortium of the Sabin Vaccine Institute (CVC/SVI) is conducting an ongoing large-scale immune monitoring harmonization program through its members and aYliated associations. This eVort was brought to life as an external validation program by conducting an international Elispot proWciency panel with 36 laboratories in 2005, and was followed by a second panel with 29 participating laboratories in 2006 allowing for application of learnings from the Wrst panel. Critical protocol choices, as well as standardization and validation practices among laboratories were assessed through detailed surveys. Although panel participants had to follow general guidelines in order to allow comparison of results, each laboratory was able to use its own protocols, materials and reagents. The second panel recorded an overall signiWcantly improved performance, as measured by the ability to detect all predeWned responses correctly. Protocol choices and laboratory practices, which can have a dramatic eVect on the overall assay outcome, were identiWed and lead to the following recommendations: (A) Establish a laboratory SOP for Elispot testing procedures including (A1) a counting method for apoptotic cells for determining adequate cell dilution for plating, and (A2) Cancer Immunol Immunother (2008) 57:303-315 123 optimized for low background: high signal ratio, (C) Establish a laboratory SOP for plate reading including (C1) human auditing during the reading process and (C2) adequate adjustments for technical artifacts, and (D) Only allow trained personnel, which is certiWed per laboratory SOPs to conduct assays. Recommendations described under (A) were found to make a statistically signiWcant diVerence in assay performance, while the remaining recommendations are based on practical experiences conWrmed by the panel results, which could not be statistically tested. These results provide initial harmonization guidelines to optimize Elispot assay performance to the immunotherapy community. Further optimization is in process with ongoing panels.