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The transition to managed care raises concerns about the resulting quality of care. The report card, a publicly released, standardized report on quality, has received widespread acceptance as a method to evaluate physician performance. Current report cards provide insufficient information to allow purchasers of health care to assess accurately the performance of professionals who provide breast care. To overcome these limitations, we propose an expanded report card on breast cancer care. Mammographers and general surgeons would assess an independent series of at least 100 consecutive cases of newly diagnosed breast cancer. Mammographers would determine the percentage of invasive cancers < 15 mm detected on screening mammograms in asymptomatic women aged 50 to 74 years. Surgeons would determine the percentage of combined stages 0 and 1 breast cancers detected and the percentage of patients receiving breast-conserving surgical therapy. Performance targets are set at 60% for invasive cancers < 15 mm detected on screening mammography, 60% for combined stage 0 and 1 breast cancers, and 50% for patients receiving breast-conserving therapy.

Arrhythmogenic right ventricular cardiomyopathy is a heritable heart-muscle disorder that causes progressive replacement of right ventricular myocardium by fibrofatty tissue. Mutations in genes encoding desmosomal proteins play a key role in the pathogenesis of the disease. Arrhythmogenic right ventricular cardiomyopathy (ARVC), also known as arrhythmogenic right ventricular dysplasia, is a heritable heart-muscle disorder that predominantly affects the right ventricle. Progressive loss of right ventricular myocardium and its replacement by fibrofatty tissue is the pathological hallmark of the disease. 1 ARVC is one of the leading causes of arrhythmic cardiac arrest in young people and athletes. Since the original report by Marcus and colleagues was published in 1982, describing 24 affected patients, 2 there have been substantial advances in our understanding of the pathogenesis, clinical manifestations, and long-term outcome of the disorder. The disease was initially designated as a . . .

N-mixture models describe count data replicated in time and across sites in terms of abundance N and detectability p. They are popular because they allow inference about N while controlling for factors that influence p without the need for marking animals. Using a capture-recapture perspective, we show that the loss of information that results from not marking animals is critical, making reliable statistical modeling of N and p problematic using just count data. One cannot reliably fit a model in which the detection probabilities are distinct among repeat visits as this model is overspecified. This makes uncontrolled variation in p problematic. By counter example, we show that even if p is constant after adjusting for covariate effects (the \"constant p\" assumption) scientifically plausible alternative models in which N (or its expectation) is non-identifiable or does not even exist as a parameter, lead to data that are practically indistinguishable from data generated under an N-mixture model. This is particularly the case for sparse data as is commonly seen in applications. We conclude that under the constant p assumption reliable inference is only possible for relative abundance in the absence of questionable and/or untestable assumptions or with better quality data than seen in typical applications. Relative abundance models for counts can be readily fitted using Poisson regression in standard software such as R and are sufficiently flexible to allow controlling for p through the use covariates while simultaneously modeling variation in relative abundance. If users require estimates of absolute abundance, they should collect auxiliary data that help with estimation of p.

Hematopoietic clones harboring specific mutations may expand over time. However, it remains unclear how different cellular stressors influence this expansion. Here we characterize clonal hematopoiesis after two different cellular stressors: cytotoxic therapy and hematopoietic transplantation. Cytotoxic therapy results in the expansion of clones carrying mutations in DNA damage response genes, including TP53 and PPM1D . Analyses of sorted populations show that these clones are typically multilineage and myeloid-biased. Following autologous transplantation, most clones persist with stable chimerism. However, DNMT3A mutant clones often expand, while PPM1D mutant clones often decrease in size. To assess the leukemic potential of these expanded clones, we genotyped 134 t-AML/t-MDS samples. Mutations in non- TP53 DNA damage response genes are infrequent in t-AML/t-MDS despite several being commonly identified after cytotoxic therapy. These data suggest that different hematopoietic stressors promote the expansion of distinct long-lived clones, carrying specific mutations, whose leukemic potential depends partially on the mutations they harbor. Cellular stressors can impact clonal hematopoiesis. Here, the authors explore the impact of cytotoxic therapy and hematopoietic transplantation on clonal expansion, suggesting different stressors can promote expansion of distinct long-lived clones.

N-mixture models provide an appealing alternative to mark–recapture models, in that they allow for estimation of detection probability and population size from count data, without requiring that individual animals be identified. There is, however, a cost to using the N-mixture models: inference is very sensitive to the model’s assumptions. We consider the effects of three violations of assumptions that might reasonably be expected in practice: double counting, unmodeled variation in population size over time, and unmodeled variation in detection probability over time. These three examples show that small violations of assumptions can lead to large biases in estimation. The violations of assumptions we consider are not only small qualitatively, but are also small in the sense that they are unlikely to be detected using goodness-of-fit tests. In cases where reliable estimates of population size are needed, we encourage investigators to allocate resources to acquiring additional data, such as recaptures of marked individuals, for estimation of detection probabilities.

Whole-genome sequencing of samples from seven subjects with secondary acute myeloid leukemia identified somatic mutations. These data, together with genotype analysis of the antecedent myelodysplastic syndromes (MDS), revealed the clonal evolution of MDS and secondary AML. The myelodysplastic syndromes, a heterogeneous group of diseases characterized by ineffective hematopoiesis, are the most common cause of acquired bone marrow failure in adults. 1 Secondary acute myeloid leukemia (AML) develops in approximately one third of persons with myelodysplastic syndromes. 2 Clinical discrimination between the myelodysplastic syndromes and secondary AML currently rests predominantly on cytomorphologic analysis, since patients with myelodysplastic syndromes have dysplastic hematopoiesis and a myeloblast count of less than 20%, whereas those with a myeloblast count of 20% or more have AML. Although considerable overlap exists between the spectrum of cytogenetic and molecular lesions seen in the two disorders, there . . .

Next-generation sequencing has been used to infer the clonality of heterogeneous tumor samples. These analyses yield specific predictions-the population frequency of individual clones, their genetic composition, and their evolutionary relationships-which we set out to test by sequencing individual cells from three subjects diagnosed with secondary acute myeloid leukemia, each of whom had been previously characterized by whole genome sequencing of unfractionated tumor samples. Single-cell mutation profiling strongly supported the clonal architecture implied by the analysis of bulk material. In addition, it resolved the clonal assignment of single nucleotide variants that had been initially ambiguous and identified areas of previously unappreciated complexity. Accordingly, we find that many of the key assumptions underlying the analysis of tumor clonality by deep sequencing of unfractionated material are valid. Furthermore, we illustrate a single-cell sequencing strategy for interrogating the clonal relationships among known variants that is cost-effective, scalable, and adaptable to the analysis of both hematopoietic and solid tumors, or any heterogeneous population of cells.

Systematic analysis of cancer-associated mutations in the blood cells of healthy individuals. Several genetic alterations characteristic of leukemia and lymphoma have been detected in the blood of individuals without apparent hematological malignancies. The Cancer Genome Atlas (TCGA) provides a unique resource for comprehensive discovery of mutations and genes in blood that may contribute to the clonal expansion of hematopoietic stem/progenitor cells. Here, we analyzed blood-derived sequence data from 2,728 individuals from TCGA and discovered 77 blood-specific mutations in cancer-associated genes, the majority being associated with advanced age. Remarkably, 83% of these mutations were from 19 leukemia and/or lymphoma-associated genes, and nine were recurrently mutated ( DNMT3A , TET2 , JAK2 , ASXL1 , TP53 , GNAS , PPM1D , BCORL1 and SF3B1). We identified 14 additional mutations in a very small fraction of blood cells, possibly representing the earliest stages of clonal expansion in hematopoietic stem cells. Comparison of these findings to mutations in hematological malignancies identified several recurrently mutated genes that may be disease initiators. Our analyses show that the blood cells of more than 2% of individuals (5–6% of people older than 70 years) contain mutations that may represent premalignant events that cause clonal hematopoietic expansion.

Somatic TP53 mutations are highly prevalent in therapy-related acute myeloid leukaemia and myelodysplastic syndrome, which arise as complications of cytotoxic chemotherapy or radiotherapy; although it was believed that these TP53 mutations are directly induced by cytotoxic therapy, new data indicate that they predate cytotoxic therapy and that haematopoietic progenitors harbouring these pre-existing mutations may selectively expand after exposure to chemotherapy or radiotherapy. TP53 mutations predate cytotoxic therapy The clonal haematopoietic disorders known as therapy-related acute myeloid leukaemia (t-AML) and therapy-related myelodysplastic syndrome (t-MDS) typically develop 1 to 5 years after exposure to chemotherapy or radiotherapy. TP53 mutations are selectively enriched in t-AML/t-MDS, and were thought to be directly induced by cytotoxic therapy. Now Daniel Link and colleagues present genome sequencing data that suggest the TP53 mutations predate cytotoxic therapy. It appears that rare haematopoietic stem/progenitor cells in blood or bone marrow carry age-related TP53 mutations, and that these cells undergo clonal expansion only after selective pressure applied by chemotherapy. Therapy-related acute myeloid leukaemia (t-AML) and therapy-related myelodysplastic syndrome (t-MDS) are well-recognized complications of cytotoxic chemotherapy and/or radiotherapy 1 . There are several features that distinguish t-AML from de novo AML, including a higher incidence of TP53 mutations 2 , 3 , abnormalities of chromosomes 5 or 7, complex cytogenetics and a reduced response to chemotherapy 4 . However, it is not clear how prior exposure to cytotoxic therapy influences leukaemogenesis. In particular, the mechanism by which TP53 mutations are selectively enriched in t-AML/t-MDS is unknown. Here, by sequencing the genomes of 22 patients with t-AML, we show that the total number of somatic single-nucleotide variants and the percentage of chemotherapy-related transversions are similar in t-AML and de novo AML, indicating that previous chemotherapy does not induce genome-wide DNA damage. We identified four cases of t-AML/t-MDS in which the exact TP53 mutation found at diagnosis was also present at low frequencies (0.003–0.7%) in mobilized blood leukocytes or bone marrow 3–6 years before the development of t-AML/t-MDS, including two cases in which the relevant TP53 mutation was detected before any chemotherapy. Moreover, functional TP53 mutations were identified in small populations of peripheral blood cells of healthy chemotherapy-naive elderly individuals. Finally, in mouse bone marrow chimaeras containing both wild-type and Tp53 +/− haematopoietic stem/progenitor cells (HSPCs), the Tp53 +/− HSPCs preferentially expanded after exposure to chemotherapy. These data suggest that cytotoxic therapy does not directly induce TP53 mutations. Rather, they support a model in which rare HSPCs carrying age-related TP53 mutations are resistant to chemotherapy and expand preferentially after treatment. The early acquisition of TP53 mutations in the founding HSPC clone probably contributes to the frequent cytogenetic abnormalities and poor responses to chemotherapy that are typical of patients with t-AML/t-MDS.