Identification of phenotype-relevant differentially expressed genes in breast cancer demonstrates enhanced quantile discretization protocol’s utility in multi-platform microarray data integration

2016 ◽  
Vol 14 (05) ◽  
pp. 1650022 ◽  
Author(s):  
Darlington S. Mapiye ◽  
Alan G. Christoffels ◽  
Junaid Gamieldien
Keyword(s):  
Breast Cancer ◽  
Translational Control ◽  
Statistical Power ◽  
Numerical Range ◽  
Small Sample Size ◽  
Small Sample ◽  
Differentially Expressed ◽  
Data Repositories ◽  
The Individual ◽  
Selection Of

Microarray for transcriptomics experiments often suffer from limited statistical power due to small sample size. Quantile discretization (QD) maps expression values for a sample into a series of equivalently sized ‘bins’ that represent a discrete numerical range, e.g. [Formula: see text]4 to [Formula: see text]4, which enables normalized data from multiple experiments and/or expression platforms to be combined for re-analysis. We found, however, that informal selection of bin numbers often resulted in loss of the underlying correlation structure in the data through assigning of the same numerical value to genes that are in reality expressed at significantly different levels within a sample. Here we report a procedure for determining an optimal bin number for dataset. Applying this to integrated public breast cancer datasets enabled statistical identification of several differentially expressed tumorigenesis-related genes that were not found when analyzing the individual datasets, and also several cancer biomarkers not previously indicated as having utility in the disease. Notably, differential modulation of translational control and protein synthesis via multiple pathways were found to potentially have central roles in breast cancer development and progression. These findings suggest that our protocol has significant utility in making meaningful novel biomedical discoveries by leveraging the large public expression data repositories.

scholarly journals CDK4/6 Inhibitors and Arthralgia: A Single Institution Experience

2021 ◽  
Vol 9 (2) ◽  
pp. 42
Author(s):  
Angeliki Andrikopoulou ◽  
Oraianthi Fiste ◽  
Kleoniki Apostolidou ◽  
Efthymia Skafida ◽  
Christos Markellos ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Small Sample Size ◽  
Small Sample ◽  
Musculoskeletal Symptoms ◽  
Hematological Toxicity ◽  
Breast Cancer Patients ◽  
Single Institution ◽  
Duration Of Treatment ◽  
Positive Breast Cancer

Background: Aromatase inhibitors (AIs) are associated with musculoskeletal pain in one third (20–47%) of breast cancer patients. Recently, CDK4/6 inhibitors have emerged as a new therapeutic approach in hormone receptor (HR)-positive breast cancer. While hematological and gastrointestinal toxicities are frequently reported during treatment with CDK4/6 inhibitors, musculoskeletal symptoms are less commonly encountered. Methods: Herein, we present a retrospective study of 47 breast cancer patients who received CDK4/6 inhibitors along with endocrine therapy in our department between 01/01/2018 and 01/09/2020. Results: Median age at diagnosis was 58 years (29–81). Median duration of treatment was 8.76 months (SD: 7.68; 0.47–30.13 months). Median PFS was 24.33 months (95% CI; 1.71–46.96). Overall, toxicity was reported in 61.7% of the cases (29/47). Arthralgia was reported in 6.4% (3/47) of the patients. Hematological toxicity was reported in 51.1% (24/47) of the patients. Neutropenia was the main hematological toxicity observed (86.8%; 22/47) along with anemia (4.3%; 2/47), thrombocytopenia (2.1%; 1/47), and leukopenia (4.2%; 1/24). Conclusions: Though our data reflect a small sample size, we report a reduced arthralgia rate (6.4%) during treatment with CDK4/6 inhibitors compared with that reported in studies of AIs (20–47%).

Statistical Power Analysis can Improve Fisheries Research and Management

1990 ◽  
Vol 47 (1) ◽  
pp. 2-15 ◽  
Author(s):  
Randall M. Peterman
Keyword(s):  
Sample Size ◽  
Power Analysis ◽  
Statistical Power ◽  
Small Sample Size ◽  
Industrial Effluent ◽  
Small Sample ◽  
Detectable Effect ◽  
Type Ii ◽  
Sampling Variability ◽  
Statistical Power Analysis

Ninety-eight percent of recently surveyed papers in fisheries and aquatic sciences that did not reject some null hypothesis (H0) failed to report β, the probability of making a type II error (not rejecting H0 when it should have been), or statistical power (1 – β). However, 52% of those papers drew conclusions as if H0 were true. A false H0 could have been missed because of a low-power experiment, caused by small sample size or large sampling variability. Costs of type II errors can be large (for example, for cases that fail to detect harmful effects of some industrial effluent or a significant effect of fishing on stock depletion). Past statistical power analyses show that abundance estimation techniques usually have high β and that only large effects are detectable. I review relationships among β, power, detectable effect size, sample size, and sampling variability. I show how statistical power analysis can help interpret past results and improve designs of future experiments, impact assessments, and management regulations. I make recommendations for researchers and decision makers, including routine application of power analysis, more cautious management, and reversal of the burden of proof to put it on industry, not management agencies.

Nipple Confusion

PEDIATRICS ◽  
1993 ◽  
Vol 92 (2) ◽  
pp. 300-301
Author(s):  
DOREN FREDRICKSON
Keyword(s):  
Breast Feeding ◽  
Statistical Power ◽  
White Women ◽  
Small Sample Size ◽  
False Negative ◽  
Small Sample ◽  
Bottle Feeding ◽  
Feeding Duration ◽  
Breast Feed ◽  
The Impact

To the Editor.— I wish to comment on the study reported by Cronenwett et al,1 which was a fascinating prospective study among married white women who planned to breast-feed. Women were randomly selected to perform either exdusive breast-feeding or partial breast-feeding with bottled human milk supplements to determine the impact of infant temperament and limited bottle-feeding on breast-feeding duration. The authors admit that small sample size and lack of statistical power make a false-negative possible.

The feasibility of same day pegfilgrastim-cbqv administration in breast cancer patients receiving myelosuppressive chemotherapy regimens at a northern Virginia cancer center.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18687-e18687
Author(s):  
Maya Leiva ◽  
Angela Pennisi ◽  
Kathleen Kiernan Harnden ◽  
Patricia Conrad Rizzo ◽  
Lauren Ann Mauro
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Small Sample Size ◽  
Standard Of Care ◽  
Secondary Prophylaxis ◽  
Small Sample ◽  
Cancer Center ◽  
Breast Cancer Patients ◽  
Curative Intent ◽  
Myelosuppressive Chemotherapy

e18687 Background: The long-acting injectable G-CSF, pegfilgrastim and its biosimilars have historically been given to patients 24 hours following the administration of myelosuppressive chemotherapy for either primary or secondary prophylaxis of febrile neutropenia (FN). Previous literature has indicated that pegfilgrastim administration prior to 24 hours post chemotherapy, may result in a deepened and prolonged neutropenia due to the increase in circulating granulocytes exposed to chemotherapy. With the onset of the COVID-19 pandemic and to reduce potential SAR-CoV-2 exposure to cancer patients on therapy, we implemented same day administration of injectable pegfilgrastim-cbqv among select breast cancer patients receiving myelosuppressive chemotherapy regimens from March 2020 – February 2021. Methods: Utilizing retrospective EHR chart reviews, 55 patients among 4 medical oncologists in our breast cancer group were identified as meeting the criteria of same day pegfilgrastim-cbqv administration. Inclusion was based on completion of at least 2 consecutive cycles of same day pegfilgrastim-cbqv 6 mg subcutaneous injection for primary or secondary prophylaxis. The selected patient charts were reviewed for the incidence and severity of FN. Among the patients who had documented FN, further subgroup analyses were done regarding baseline characteristics, timing of neutropenia, regimens, regimen sequence, and reported ADRs associated with pegfilgrastim-cbqv. Results: 9 (16.4%) of the 55 patients experienced FN (Grades 3-4) and 6 (10.9%) patients were hospitalized. There were no Grade 5 events and none had therapy discontinued due to FN. 8 (88.9%) of the patients experienced FN between cycles 1 and 2. Of note, there were no cases of COVID-19 among the 9 patients who had an episode of FN. 52 (94.5%) of the 55 patients received treatment with curative intent and 3 (5.5%) had metastatic disease on a subsequent line of therapy. The median age was 49.1 years (range 29-71) and patients were 56.4% Caucasian, 18.1% Black or African American, 12.7% Asian, and 12.7% Hispanic/Latina. Conclusions: Based on the retrospective data analysis, same day pegfilgrastim-cbqv appears to be a safe and effective option in the primary and secondary prophylaxis of FN with myelosuppressive standard of care chemotherapy used in breast cancer treatment. Though our review was limited by a relatively small sample size and confined to younger (49.1 median age) breast cancer patients, this opens the door to further re-evaluation of same day pegfilgrastim-cbqv administration in other patient populations. In a post pandemic treatment world, this slight change in practice has the potential to reduce patient financial toxicity associated with multiple medical visits, provide an alternative to on-body injector formulations, and ensure treatment adherence.

scholarly journals Efficient prediction of a spatial transcriptomics profile better characterizes breast cancer tissue sections without costly experimentation

2021 ◽  
Author(s):  
Taku Monjo ◽  
Masaru Koido ◽  
Satoi Nagasawa ◽  
Yutaka Suzuki ◽  
Yoichiro Kamatani
Keyword(s):  
Breast Cancer ◽  
Small Sample Size ◽  
Expression Patterns ◽  
Imputation Accuracy ◽  
Gene Clusters ◽  
Small Sample ◽  
Breast Cancer Tissue ◽  
Cancer Tissue ◽  
Gene Expressions ◽  
Tissue Sections

Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expressions in unmeasured regions and tissues can enhance biologists' histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE and confirmed its performance using the spatial-transcriptome profiles and immunohistochemistry images of consecutive human breast cancer tissue sections. For example, the predicted expression patterns of SPARC, an invasion marker, highlighted a small tumor-invasion region that is difficult to identify using raw data of spatial transcriptome alone because of a lack of measurements. We further developed semi-supervised DeepSpaCE using unlabeled histology images and increased the imputation accuracy of consecutive sections, enhancing applicability for a small sample size. Our method enables users to derive hidden histological characters via spatial transcriptome and gene annotations, leading to accelerated biological discoveries without additional experiments.

scholarly journals Combining Bayesian Approaches and Evolutionary Techniques for the Inference of Breast Cancer Networks

2017 ◽  
Author(s):  
Stefano Beretta ◽  
Mauro Castelli ◽  
Ivo Gonçalves ◽  
Ivan Merelli ◽  
Daniele Ramazzotti
Keyword(s):  
Breast Cancer ◽  
Graphical Models ◽  
Protein Interactions ◽  
Large Scale ◽  
Small Sample Size ◽  
Small Sample ◽  
Cancer Data ◽  
Correlation Networks ◽  
Model Complex ◽  
Cancer Networks

AbstractGene and protein networks are very important to model complex large-scale systems in molecular biology. Inferring or reverseengineering such networks can be defined as the process of identifying gene/protein interactions from experimental data through computational analysis. However, this task is typically complicated by the enormously large scale of the unknowns in a rather small sample size. Furthermore, when the goal is to study causal relationships within the network, tools capable of overcoming the limitations of correlation networks are required. In this work, we make use of Bayesian Graphical Models to attach this problem and, specifically, we perform a comparative study of different state-of-the-art heuristics, analyzing their performance in inferring the structure of the Bayesian Network from breast cancer data.

scholarly journals Comparison of statistical methods for analysis of small sample sizes for detecting the differences in efficacy between treatments for knee osteoarthritis

2020 ◽  
Author(s):  
Chia-Lung Shih ◽  
Te-Yu Hung
Keyword(s):  
Knee Osteoarthritis ◽  
Sample Size ◽  
Statistical Methods ◽  
Statistical Power ◽  
Permutation Test ◽  
Small Sample Size ◽  
Small Sample ◽  
T Test ◽  
Sample Sizes ◽  
Knee Oa

Abstract Background A small sample size (n < 30 for each treatment group) is usually enrolled to investigate the differences in efficacy between treatments for knee osteoarthritis (OA). The objective of this study was to use simulation for comparing the power of four statistical methods for analysis of small sample size for detecting the differences in efficacy between two treatments for knee OA. Methods A total of 10,000 replicates of 5 sample sizes (n=10, 15, 20, 25, and 30 for each group) were generated based on the previous reported measures of treatment efficacy. Four statistical methods were used to compare the differences in efficacy between treatments, including the two-sample t-test (t-test), the Mann-Whitney U-test (M-W test), the Kolmogorov-Smirnov test (K-S test), and the permutation test (perm-test). Results The bias of simulated parameter means showed a decreased trend with sample size but the CV% of simulated parameter means varied with sample sizes for all parameters. For the largest sample size (n=30), the CV% could achieve a small level (<20%) for almost all parameters but the bias could not. Among the non-parametric tests for analysis of small sample size, the perm-test had the highest statistical power, and its false positive rate was not affected by sample size. However, the power of the perm-test could not achieve a high value (80%) even using the largest sample size (n=30). Conclusion The perm-test is suggested for analysis of small sample size to compare the differences in efficacy between two treatments for knee OA.

Impact of race on biomarker testing among HER2- advanced breast cancer (ABC) patients (pts) in the United States: Results from a real-world study.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 10598-10598
Author(s):  
Reshma L. Mahtani ◽  
Alexander Niyazov ◽  
Katie Lewis ◽  
Lucy Massey ◽  
Alex Rider ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Targeted Therapies ◽  
Small Sample Size ◽  
The United States ◽  
Small Sample ◽  
Access To Treatment ◽  
History Of ◽  
Biomarker Testing ◽  
Abstract Data ◽  
The Impact

10598 Background: African Americans (AA) have the highest breast cancer (BC) mortality rate. Access to treatment is a known contributing factor. In the past 4 years, several targeted therapies for HER2- BC have become available which require testing for specific biomarkers. This study assessed the impact of race on biomarker testing rates in HER2- ABC pts receiving treatment in the US. Methods: Oncologists were recruited to abstract data from medical charts for the next 8-10 pts receiving treatment with HER2- ABC during Sept 2019-Apr 2020. Pts records were stratified by race and categorized into 3 mutually exclusive cohorts [White/Caucasian (White), AA, Other]. The other race cohort was excluded from this analysis due to small sample size. Differences in pt demographics/clinical characteristics were analyzed via Fisher’s exact tests. Testing rates for actionable biomarkers (i.e. BRCA1/2, PIK3CA, PD-L1) were compared between White and AA pts utilizing logistic regressions controlling for age, known family history of a BRCA-related cancer, hormone receptor (HR) status and practice setting (academic vs. community). Further analyses by age will be presented. Results: This analysis included 378 pts records, provided by 40 oncologists. Mean age was 64 years; 77% had HR+/HER2- ABC; 20% had advanced triple negative breast cancer (TNBC), 3% had ABC with an unknown HR status. Compared to White pts, AA pts were significantly more likely to have advanced TNBC (27% vs. 18%, p<0.05). Compared to White pts, AA pts had significantly lower BRCA1/2 mutation (mut) testing rates (Table). Numerically lower rates of PIK3CAmut and PD-L1 testing were observed among AA pts (Table). BRCA1/2mut positivity rate (germline [g] and/or somatic [s]) was higher among AA vs. White pts (30% vs. 22%). Positivity rate for PIK3CAmut was lower for AA vs. White pts (8% vs. 11%). Conclusions: A higher than expected BRCA1/2mut positivity rate was observed than previously reported in the literature. This is likely because this analysis included s BRCA1/2mut and represented a high risk pt population. Across all biomarkers assessed, AA pts had lower testing rates than White pts. This suggests racial disparities in testing rates of actionable biomarkers. Consistent with guidelines, and with the increased availability of targeted therapies, focused efforts should be developed to increase biomarker testing in AA pts. Funding: Pfizer Biomarker Testing Rates by Race.[Table: see text]

Three-year results of phase I retinal gene therapy trial for CNGA3-mutated achromatopsia: results of a non randomised controlled trial

2021 ◽  
pp. bjophthalmol-2021-319067
Author(s):  
Felix Friedrich Reichel ◽  
Stylianos Michalakis ◽  
Barbara Wilhelm ◽  
Ditta Zobor ◽  
Regine Muehlfriedel ◽  
...  
Keyword(s):  
Gene Therapy ◽  
Primary Endpoint ◽  
Statistical Power ◽  
Small Sample Size ◽  
Controlled Trial ◽  
Statistical Significance ◽  
Small Sample ◽  
Functional Improvement ◽  
Limiting Factor ◽  
Serious Adverse Events

AimsTo determine long-term safety and efficacy outcomes of a subretinal gene therapy for CNGA3-associated achromatopsia. We present data from an open-label, nonrandomised controlled trial (NCT02610582).MethodsDetails of the study design have been previously described. Briefly, nine patients were treated in three escalating dose groups with subretinal AAV8.CNGA3 gene therapy between November 2015 and October 2016. After the first year, patients were seen on a yearly basis. Safety assessment constituted the primary endpoint. On a secondary level, multiple functional tests were carried out to determine efficacy of the therapy.ResultsNo adverse or serious adverse events deemed related to the study drug occurred after year 1. Safety of the therapy, as the primary endpoint of this trial, can, therefore, be confirmed. The functional benefits that were noted in the treated eye at year 1 were persistent throughout the following visits at years 2 and 3. While functional improvement in the treated eye reached statistical significance for some secondary endpoints, for most endpoints, this was not the case when the treated eye was compared with the untreated fellow eye.ConclusionThe results demonstrate a very good safety profile of the therapy even at the highest dose administered. The small sample size limits the statistical power of efficacy analyses. However, trial results inform on the most promising design and endpoints for future clinical trials. Such trials have to determine whether treatment of younger patients results in greater functional gains by avoiding amblyopia as a potential limiting factor.

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