Updated analysis of CALGB (Alliance) 100104 assessing lenalidomide versus placebo maintenance after single autologous stem-cell transplantation for multiple myeloma: a randomised, double-blind, phase 3 trial.

BACKGROUND: In the CALGB (Alliance) 100104 study, lenalidomide versus placebo after autologous stem-cell transplantation (ASCT) was investigated for patients with newly diagnosed myeloma. That study showed improved time to progression and overall survival and an increase in second primary malignancies for lenalidomide at a median follow-up of 34 months. Here we report an updated intention-to-treat analysis of CALGB (Alliance) 100104 at a median follow-up of 91 months. METHODS: Patients were eligible for this randomised, double-blind, placebo-controlled, phase 3 trial if they had symptomatic disease requiring treatment; had received, at most, two induction regimens; and had achieved stable disease or better in the first 100 days after ASCT. We randomly assigned patients to either lenalidomide or placebo groups using permuted block randomisation, with a fixed block size of six. Randomisation was stratified by three factors: normal or elevated ß2 microglobulin concentration at registration (≤2·5 mg/L vs >2·5 mg/L), previous use or non-use of thalidomide during induction therapy, and previous use or non-use of lenalidomide during induction therapy. The starting dose was two capsules (10 mg) per day, escalated to three capsules (15 mg) per day after 3 months. The primary endpoint was time to progression (time of progressive disease or death from any cause), with intention-to-treat analysis. This study is registered with ClinicalTrials.gov, identifier NCT00114101. New patients are no longer being recruited, but some patients remain on treatment and in follow-up. FINDINGS: Between April 14, 2005, and July 2, 2009, 460 patients were randomly assigned to receive either lenalidomide (n=231) or placebo (n=229). After three interim analyses, the study was unblinded at a median follow-up of 18 months, at which point 86 (67%) of 128 patients without progressive disease in the placebo group chose to cross over to the lenalidomide group. The median follow-up for the updated survival analysis, as of Oct 19, 2016, was 91 months (IQR 83·6-103·1). The median time to progression was 57·3 months (95% CI 44·2-73·3) for the lenalidomide group and 28·9 months (23·0-36·3) for the placebo group (hazard ratio 0·57, 95% CI 0·46-0·71; p<0·0001). The most common grade 3-4 adverse events were neutropenia (116 [50%] patients in the lenalidomide group and 41 [18%] patients in the placebo group) and thrombocytopenia (34 [15%] patients in the lenalidomide group and 12 [5%] patients in the placebo group). 18 (8%) haematological and 14 (6%) solid tumour second primary malignancies were diagnosed after randomisation and before disease progression in the lenalidomide group, compared with three (1%) haematological and nine (4%) solid tumour second primary malignancies in the placebo group. Three haematological and five solid tumour second primary malignancies in the placebo group were in the crossover subgroup. INTERPRETATION: Despite an increase in haematological adverse events and second primary malignancies, lenalidomide maintenance therapy after ASCT significantly improved time to progression and could be considered a standard of care. FUNDING: The National Cancer Institute.

Predicting BRCA1 and BRCA2 gene mutation carriers: comparison of PENN II model to previous study.

A number of models have been developed to predict the probability that a person carries a detectable germline mutation in the BRCA1 or BRCA2 genes. Their relative performance in a clinical setting is variable. To compare the performance characteristics of a web-based BRCA1/BRCA2 gene mutation prediction model: the PENNII model ( www.afcri.upenn.edu/itacc/penn2 ), with studies done previously at our institution using four other models including LAMBDA, BRCAPRO, modified PENNI (Couch) tables, and Myriad II tables collated by Myriad Genetics Laboratories. Proband and family cancer history data were analyzed from 285 probands from unique families (27 Ashkenazi Jewish; 277 female) seen for genetic risk assessment in a multispecialty tertiary care group practice. All probands had clinical testing for BR.CA1 and BRCA2 mutations conducted in the same single commercial laboratory. The performance for PENNII results were assessed by the area under the receiver operating characteristic curve (AUC) of sensitivity versus 1-specificity, as a measure of ranking. The AUCs of the PENNII model were higher for predicting BRCA1 than for BRCA2 (81 versus 72%). The overall AUC was 78.7%. PENN II model for BRCA1/2 prediction performed well in this population with higher AUC compared with our experience using four other models. The ease of use of the PENNII model is compatible with busy clinical practices.

Predicting BRCA1 and BRCA2 gene mutation carriers: comparison of LAMBDA, BRCAPRO, Myriad II, and modified Couch models.

CONTEXT: Models have been developed to predict the probability that a person carries a detectable germline mutation in the BRCA1 or BRCA2 genes. Their relative performance in a clinical setting is unclear. OBJECTIVE: To compare the performance characteristics of four BRCA1/BRCA2 gene mutation prediction models: LAMBDA, based on a checklist and scores developed from data on Ashkenazi Jewish (AJ) women; BRCAPRO, a Bayesian computer program; modified Couch tables based on regression analyses; and Myriad II tables collated by Myriad Genetics Laboratories. DESIGN AND SETTING: Family cancer history data were analyzed from 200 probands from the Mayo Clinic Familial Cancer Program, in a multispecialty tertiary care group practice. All probands had clinical testing for BRCA1 and BRCA2 mutations conducted in a single laboratory. MAIN OUTCOMES MEASURES: For each model, performance was assessed by the area under the receiver operator characteristic curve (ROC) and by tests of accuracy and dispersion. Cases "missed" by one or more models (model predicted less than 10% probability of mutation when a mutation was actually found) were compared across models. RESULTS: All models gave similar areas under the ROC curve of 0.71 to 0.76. All models except LAMBDA substantially under-predicted the numbers of carriers. All models were too dispersed. CONCLUSIONS: In terms of ranking, all prediction models performed reasonably well with similar performance characteristics. Model predictions were widely discrepant for some families. Review of cancer family histories by an experienced clinician continues to be vital to ensure that critical elements are not missed and that the most appropriate risk prediction figures are provided.

Desmoid tumors -- a characterization of patients seen at Mayo Clinic 1976-1999.

Desmoid tumors occur with high frequency in individuals with Familial Adenomatous Polyposis (FAP). Because of this, individuals developing desmoid tumors may be referred for genetic risk assessment. Determining whether a person has a FAP-related desmoid tumor or a sporadic desmoid can be challenging. We sought to characterize the patients who were seen at our institution to determine if there were clinical differences in presentation between FAP-associated and sporadic desmoid tumors. We searched the Mayo Clinic-modified H-ICDA (Hospital adaptation of the International Classification of Diseases) diagnostic codes for all diagnoses of desmoid tumors in patients seen between 1976 and 1999. Charts were reviewed to determine accuracy of diagnosis, age when seen, gender, site of tumor, and presence of polyposis. A total of 454 patients (174 males and 280 females) met the search criterion. Of the 447 patients on whom all data was obtained, 70 had FAP and 377 had no evidence of FAP. The female/male ratio for FAP cases was 1.12 compared to female/male ratio of 1.71 for non-FAP cases. (P=0.17). Location of development of desmoid tumors was correlated with but not specific for distinguishing FAP from non-FAP desmoids. Abdominal desmoids comprised the majority of FAP desmoids and extra-abdominal desmoids comprised the majority of non-FAP desmoids (P<0.001) but age was not a discriminating factor. Using Bayesian analysis, we demonstrate how these findings can assist genetic professionals in their evaluation of patients with desmoid tumors by providing prior probabilities of FAP based upon clinical presentation.