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The Statistical Consulting Center for Astronomy (SCCA)

The process by which raw astronomical data acquisition is transformed into scientifically meaningful results and interpretation typically involves many statistical steps. Traditional astronomy limits itself to a narrow range of old and familiar statistical methods: means and standard deviations; least-squares methods like chi(sup 2) minimization; and simple nonparametric procedures such as the Kolmogorov-Smirnov tests. These tools are often inadequate for the complex problems and datasets under investigations, and recent years have witnessed an increased usage of maximum-likelihood, survival analysis, multivariate analysis, wavelet and advanced time-series methods. The Statistical Consulting Center for Astronomy (SCCA) assisted astronomers with the use of sophisticated tools, and to match these tools with specific problems. The SCCA operated with two professors of statistics and a professor of astronomy working together. Questions were received by e-mail, and were discussed in detail with the questioner. Summaries of those questions and answers leading to new approaches were posted on the Web (www.state.psu.edu/ mga/SCCA). In addition to serving individual astronomers, the SCCA established a Web site for general use that provides hypertext links to selected on-line public-domain statistical software and services. The StatCodes site (www.astro.psu.edu/statcodes) provides over 200 links in the areas of: Bayesian statistics; censored and truncated data; correlation and regression, density estimation and smoothing, general statistics packages and information; image analysis; interactive Web tools; multivariate analysis; multivariate clustering and classification; nonparametric analysis; software written by astronomers; spatial statistics; statistical distributions; time series analysis; and visualization tools. StatCodes has received a remarkable high and constant hit rate of 250 hits/week (over 10,000/year) since its inception in mid-1997. It is of interest to scientists both within and outside of astronomy. The most popular sections are multivariate techniques, image analysis, and time series analysis. Hundreds of copies of the ASURV, SLOPES and CENS-TAU codes developed by SCCA scientists were also downloaded from the StatCodes site. In addition to formal SCCA duties, SCCA scientists continued a variety of related activities in astrostatistics, including refereeing of statistically oriented papers submitted to the Astrophysical Journal, talks in meetings including Feigelson's talk to science journalists entitled "The reemergence of astrostatistics" at the American Association for the Advancement of Science meeting, and published papers of astrostatistical content.

Akritas, Michael↗

Prognostic Significance of the Number of Positive Lymph Nodes in Women With T1-2N1 Breast Cancer Treated With Mastectomy: Should Patients With 1, 2, and 3 Positive Lymph Nodes Be Grouped Together?

Purpose: To determine whether patients with 1, 2, or 3 positive lymph nodes (LNs) have similar survival outcomes. Methods and Materials: We analyzed the Surveillance, Epidemiology, and End Results registry of breast cancer patients diagnosed between 1990 and 2003. We identified 10,415 women with T1-2N1M0 breast cancer who were treated with mastectomy with no adjuvant radiation, with at least 10 LNs examined and 6 months of follow-up. The Kaplan-Meier method and log–rank test were used for survival analysis. Multivariate analysis was performed using the Cox proportional hazard model. Results: Median follow-up was 92 months. Ten-year overall survival (OS) and cause-specific survival (CSS) were progressively worse with increasing number of positive LNs. Survival rates were 70%, 64%, and 60% (OS), and 82%, 76%, and 72% (CSS) for 1, 2, and 3 positive LNs, respectively. Pairwise log–rank test P values were <.001 (1 vs 2 positive LNs), <.001 (1 vs 3 positive LNs), and .002 (2 vs 3 positive LNs). Multivariate analysis showed that number of positive LNs was a significant predictor of OS and CSS. Hazard ratios increased with the number of positive LNs. In addition, age, primary tumor size, grade, estrogen receptor and progesterone receptor status, race, and year of diagnosis were significant prognostic factors. Conclusions: Our study suggests that patients with 1, 2, and 3 positive LNs have distinct survival outcomes, with increasing number of positive LNs associated with worse OS and CSS. The conventional grouping of 1-3 positive LNs needs to be reconsidered.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

A Study of Pseudoprogression After Spine Stereotactic Body Radiation Therapy

Purpose: To determine the incidence of pseudoprogression (PP) after spine stereotactic body radiation therapy based on a detailed and quantitative assessment of magnetic resonance imaging (MRI) morphologic tumor alterations, and to identify predictive factors distinguishing PP from local recurrence (LR). Methods and Materials: A retrospective analysis of 35 patients with 49 spinal segments treated with spine stereotactic body radiation therapy, from 2009 to 2014, was conducted. The median number of follow-up MRI studies was 4 (range, 2-7). The gross tumor volumes (GTVs) within each of the 49 spinal segments were contoured on the pretreatment and each subsequent follow-up T1- and T2-weighted MRI sagittal sequence. T2 signal intensity was reported as the mean intensity of voxels constituting each volume. LR was defined as persistent GTV enlargement on ≥2 serial MRI studies for ≥6 months or on pathologic confirmation. PP was defined as a GTV enlargement followed by stability or regression on subsequent imaging within 6 months. Kaplan-Meier analysis was used for estimation of actuarial local control, disease-free survival, and overall survival. Results: The median follow-up was 23 months (range, 1-39 months). PP was identified in 18% of treated segments (9 of 49) and LR in 29% (14 of 49). Earlier volume enlargement (5 months for PP vs 15 months for LR, P=.005), greater GTV to reference nonirradiated vertebral body T2 intensity ratio (+30% for PP vs −10% for LR, P=.005), and growth confined to 80% of the prescription isodose line (80% IDL) (8 of 9 PP cases vs 1 of 14 LR cases, P=.002) were associated with PP on univariate analysis. Multivariate analysis confirmed an earlier time to volume enlargement and growth within the 80% IDL as significant predictors of PP. LR involved the epidural space in all but 1 lesion, whereas PP was confined to the vertebral body in 7 of 9 cases. Conclusions: PP was observed in 18% of treated spinal segments. Tumor growth confined to the 80% IDL and earlier time to tumor enlargement were predictive for PP.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Interval Between Hysterectomy and Start of Radiation Treatment Is Predictive of Recurrence in Patients With Endometrial Carcinoma

Purpose: Adjuvant radiation therapy (RT) has been shown to improve local control in patients with endometrial carcinoma. We analyzed the impact of the time interval between hysterectomy and RT initiation in patients with endometrial carcinoma. Methods and Materials: In this institutional review board-approved study, we identified 308 patients with endometrial carcinoma who received adjuvant RT after hysterectomy. All patients had undergone hysterectomy, oophorectomy, and pelvic and para-aortic lymph node evaluation from 1988 to 2010. Patients' demographics, pathologic features, and treatments were compared. The time interval between hysterectomy and the start of RT was calculated. The effects of time interval on recurrence-free (RFS), disease-specific (DSS), and overall survival (OS) were calculated. Following univariate analysis, multivariate modeling was performed. Results: The median age and follow-up for the study cohort was 65 years and 72 months, respectively. Eighty-five percent of the patients had endometrioid carcinoma. RT was delivered with high-dose-rate brachytherapy alone (29%), pelvic RT alone (20%), or both (51%). Median time interval to start RT was 42 days (range, 21-130 days). A total of 269 patients (74%) started their RT <9 weeks after undergoing hysterectomy (group 1) and 26% started ≥9 weeks after surgery (group 2). There were a total of 43 recurrences. Tumor recurrence was significantly associated with treatment delay of ≥9 weeks, with 5-year RFS of 90% for group 1 compared to only 39% for group 2 (P<.001). On multivariate analysis, RT delay of ≥9 weeks (P<.001), presence of lymphovascular space involvement (P=.001), and higher International Federation of Gynecology and Obstetrics grade (P=.012) were independent predictors of recurrence. In addition, RT delay of ≥9 weeks was an independent significant predictor for worse DSS and OS (P=.001 and P=.01, respectively). Conclusions: Delay in administering adjuvant RT after hysterectomy was associated with worse survival endpoints. Our data suggest that shorter time interval between hysterectomy and start of RT may be beneficial.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Pulmonary Toxicity in Stage III Non-Small Cell Lung Cancer Patients Treated With High-Dose (74 Gy) 3-Dimensional Conformal Thoracic Radiotherapy and Concurrent Chemotherapy Following Induction Chemotherapy: A Secondary Analysis of Cancer and Leukemia Group B (CALGB) Trial 30105

Purpose: Cancer and Leukemia Group B (CALGB) 30105 tested two different concurrent chemoradiotherapy platforms with high-dose (74 Gy) three-dimensional conformal radiotherapy (3D-CRT) after two cycles of induction chemotherapy for Stage IIIA/IIIB non-small cell lung cancer (NSCLC) patients to determine if either could achieve a primary endpoint of >18-month median survival. Final results of 30105 demonstrated that induction carboplatin and gemcitabine and concurrent gemcitabine 3D-CRT was not feasible because of treatment-related toxicity. However, induction and concurrent carboplatin/paclitaxel with 74 Gy 3D-CRT had a median survival of 24 months, and is the basis for the experimental arm in CALGB 30610/RTOG 0617/N0628. We conducted a secondary analysis of all patients to determine predictors of treatment-related pulmonary toxicity. Methods and Materials: Patient, tumor, and treatment-related variables were analyzed to determine their relation with treatment-related pulmonary toxicity. Results: Older age, higher N stage, larger planning target volume (PTV)1, smaller total lung volume/PTV1 ratio, larger V20, and larger mean lung dose were associated with increasing pulmonary toxicity on univariate analysis. Multivariate analysis confirmed that V20 and nodal stage as well as treatment with concurrent gemcitabine were associated with treatment-related toxicity. A high-risk group comprising patients with N3 disease and V20 >38% was associated with 80% of Grades 3-5 pulmonary toxicity cases. Conclusions: Elevated V20 and N3 disease status are important predictors of treatment related pulmonary toxicity in patients treated with high-dose 3D-CRT and concurrent chemotherapy. Further studies may use these metrics in considering patients for these treatments.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Dataset_for_Conserved_macromolecular_architecture_of_Poplar_secondary_cell_walls_revealed_by_ssNMR_and_atomistic_modeling

This dataset contains solid-state 13C NMR data and atomistic molecular dynamics simulation files supporting the study of nanoscale secondary cell wall architecture across 13 genetically diverse Populus trichocarpa genotypes grown under uniform greenhouse conditions in 13C-enriched CO2 atmospheres (~89% 13C enrichment).The dataset contains two collections of solid-state 13C NMR data. (1) 200 MHz data (Bruker Avance III HD, 4 mm HX probe, 10 kHz MAS): raw Bruker TopSpin experiment folders and DMFIT-exported ascii spectra for selective and non-selective 1D 13C-13C spin diffusion experiments (3000 ms mixing) used to quantify inter-polymer spatial proximities, and short-mixing (1 ms) reference spectra used for polymeric abundance quantification by spectral deconvolution. (2) 600 MHz data (Bruker Avance III, 1.6 mm PhoenixNMR HXY probe, 30 kHz MAS): raw Bruker TopSpin experiment folders containing 2D CORD, 2D CP-INADEQUATE, and 13C/1H relaxation (T1, T1rho) experiments for all 13 genotypes, with processed Excel workbooks per experiment type. Molecular dynamics simulation code, coordinate files, and analysis scripts (NAMD/CHARMM/Python) for six atomistic cell wall models are included. Summarized ssNMR data are compiled into a single excel file and subjected to statistical analysis. Multivariate analysis code (PCA, Pearson correlation) and summary data are provided as excel worksheets and Jupyter notebooks (Python 3).

09 BIOMASS FUELS↗

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1 x Sex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Synthesis route attribution of sulfur mustard by multivariate data analysis of chemical signatures

A multivariate model was developed here to attribute samples to a synthetic method used in the production of sulfur mustard (HD). Eleven synthetic methods were used to produce 66 samples for model construction. Three chemists working in both participating laboratories took part in the production, with the aim to introduce variability while reducing the influence of laboratory or chemist specific impurities in multivariate analysis. A gas chromatographic/mass spectrometric data set of peak areas for 103 compounds was subjected to orthogonal partial least squares - discriminant analysis to extract chemical attribution signature profiles and to construct multivariate models for classification of samples. For one- and two-step routes, model quality allowed the classification of an external test set (16/16 samples) according to synthesis conditions in the reaction yielding sulfur mustard. Classification of samples according to first-step methodology was considerably more difficult, given the high purity and uniform quality of the intermediate thiodiglycol produced in the study. Model performance in classification of aged samples was also investigated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stereotactic Body Radiation Therapy and the Influence of Chemotherapy on Overall Survival for Large (≥5 Centimeter) Non-Small Cell Lung Cancer

Purpose: Stereotactic body radiation therapy (SBRT) for ≥5 cm lesions is poorly defined, largely owing to the low sample sizes in existing studies. The present analysis examined the SBRT outcomes and assessed the effect of chemotherapy in this population. Methods and Materials: The National Cancer Data Base was queried for primary non-small cell lung cancer ≥5 cm treated with SBRT (≤10 fractions). Patient, tumor, and treatment parameters were extracted. The primary outcome was overall survival (OS). Statistical methods involved Kaplan-Meier analysis and multivariable Cox proportional hazards modeling. Results: From 2004 to 2012, data from 201 patients were analyzed. The median follow-up was 41.1 months. The median tumor size was 5.5 cm (interquartile range 5.0-6.0), with cT2a, cT2b, and cT3 disease in 24.9%, 53.2%, and 21.9%, respectively. The median total SBRT dose and fractionation was 50 Gy in 4 fractions, and 92.5% of the patients underwent SBRT with ≤5 fractions. The median OS was 25.1 months. Of the 201 patients, 15% received chemotherapy. The receipt of chemotherapy was associated with longer OS (median 30.6 vs 23.4 months; P=.027). On multivariable analysis, worse OS was seen with increasing age (hazard ratio [HR] 1.03; P=.012), poorly differentiated tumors (HR 2.06; P=.049), and T3 classification (HR 2.13; P=.005). On multivariable analysis, chemotherapy remained independently associated with improved OS (HR 0.57; P=.039). Conclusions: SBRT has utility in the setting of tumors ≥5 cm, with chemotherapy associated with improved OS in this subset. These hypothesis-generating data now raise the necessity of performing prospective analyses to determine whether chemotherapy confers outcome benefits after SBRT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Short-term Androgen-Deprivation Therapy Improves Prostate Cancer-Specific Mortality in Intermediate-Risk Prostate Cancer Patients Undergoing Dose-Escalated External Beam Radiation Therapy

Purpose: We investigated the benefit of short-term androgen-deprivation therapy (ADT) in patients with intermediate-risk prostate cancer (PC) receiving dose-escalated external beam radiation therapy. Methods and Materials: The present retrospective study comprised 710 intermediate-risk PC patients receiving external beam radiation therapy with doses of ≥81 Gy at a single institution from 1992 to 2005, including 357 patients receiving neoadjuvant and concurrent ADT. Prostate-specific antigen recurrence-free survival (PSA-RFS) and distant metastasis (DM) were compared using the Kaplan-Meier method and Cox proportional hazards models. PC-specific mortality (PCSM) was assessed using competing-risks analysis. Results: The median follow-up was 7.9 years. Despite being more likely to have higher PSA levels, Gleason score 4 + 3 = 7, multiple National Comprehensive Cancer Network intermediate-risk factors, and older age (P≤.001 for all comparisons), patients receiving ADT had improved PSA-RFS (hazard ratio [HR], 0.598; 95% confidence interval [CI], 0.435-0.841; P=.003), DM (HR, 0.424; 95% CI, 0.219-0.819; P=.011), and PCSM (HR, 0.380; 95% CI, 0.157-0.921; P=.032) on univariate analysis. Using multivariate analysis, ADT was an even stronger predictor of improved PSA-RFS (adjusted HR [AHR], 0.516; 95% CI, 0.360-0.739; P<.001), DM (AHR, 0.347; 95% CI, 0.176-0.685; P=.002), and PCSM (AHR, 0.297; 95% CI, 0.128-0.685; P=.004). Gleason score 4 + 3 = 7 and ≥50% positive biopsy cores were other independent predictors of PCSM. Conclusions: Short-term ADT improves PSA-RFS, DM, and PCSM in patients with intermediate-risk PC undergoing dose-escalated external beam radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Analysis/forecast experiments with a multivariate statistical analysis scheme using FGGE data

A three-dimensional, multivariate, statistical analysis method, optimal interpolation (OI) is described for modeling meteorological data from widely dispersed sites. The model was developed to analyze FGGE data at the NASA-Goddard Laboratory of Atmospherics. The model features a multivariate surface analysis over the oceans, including maintenance of the Ekman balance and a geographically dependent correlation function. Preliminary comparisons are made between the OI model and similar schemes employed at the European Center for Medium Range Weather Forecasts and the National Meteorological Center. The OI scheme is used to provide input to a GCM, and model error correlations are calculated for forecasts of 500 mb vertical water mixing ratios and the wind profiles. Comparisons are made between the predictions and measured data. The model is shown to be as accurate as a successive corrections model out to 4.5 days.

Baker, W. E.↗

Enhancing e-waste estimates: Improving data quality by multivariate Input–Output Analysis

Highlights: • A multivariate Input–Output Analysis method for e-waste estimates is proposed. • Applying multivariate analysis to consolidate data can enhance e-waste estimates. • We examine the influence of model selection and data quality on e-waste estimates. • Datasets of all e-waste related variables in a Dutch case study have been provided. • Accurate modeling of time-variant lifespan distributions is critical for estimate. - Abstract: Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lack of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate Input–Output Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e-waste estimation studies.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Application of Multivariate Data Analysis Techniques for the Portable Isotopic Neutron Spectroscopy system

The Portable Isotopic Neutron Spectroscopy (PINS) is a commercialized system developed by Idaho National Laboratory (INL) to examine chemical compounds non-destructively, utilizing Prompt Gamma Neutron Activation Analysis (PGNAA) techniques. The PINS systems have been successfully deployed around the world to identify chemical munitions and containers. The PINS system takes advantage of a high-resolution gamma-ray spectrum from a high-purity germanium (HPGe) detector, and gamma-ray peak analysis provides input to its chemical identification logic with the probabilistic decision tree (PDT). Gamma-ray peak analyses, however, require knowledge of pre-selected gamma-ray peaks whose energies, intensities, and origins are well studied, and some peaks might be excluded from the decision making processes due to lack of current nuclear data. In contrast, Multivariate Analysis (MVA) treats a whole gamma-ray spectrum as a collection of multiple variables or a pattern. The effectiveness of chemical identification algorithm is determined by the availability of a wide range of data to train an algorithm to identify chemical fills with accuracy. INL has a collection of gamma-ray spectra of various chemical-fills from the field-deployed PINS systems over the years, and it was envisaged to combine such a database with the principle of multivariate statistics. Therefore, in parallel with the current decision tree algorithm, an MVA-based chemical identification algorithm was developed as an independent verification of the current results. The Principal Component Analysis (PCA) method was adopted to build an MVA-based identification algorithm, using the collected field data to refine and validate the algorithm. A benchmarking study of the MVA-based algorithm’s performance was conducted alongside the current algorithm, with the results presented and discussed in this study.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Multivariate statistical analysis: Principles and applications to coorbital streams of meteorite falls

Multivariate statistical analysis techniques (linear discriminant analysis and logistic regression) can provide powerful discrimination tools which are generally unfamiliar to the planetary science community. Fall parameters were used to identify a group of 17 H chondrites (Cluster 1) that were part of a coorbital stream which intersected Earth's orbit in May, from 1855 - 1895, and can be distinguished from all other H chondrite falls. Using multivariate statistical techniques, it was demonstrated that a totally different criterion, labile trace element contents - hence thermal histories - or 13 Cluster 1 meteorites are distinguishable from those of 45 non-Cluster 1 H chondrites. Here, we focus upon the principles of multivariate statistical techniques and illustrate their application using non-meteoritic and meteoritic examples.

Wolf, S. F.↗

Prognostic Impact of the 6th and 7th American Joint Committee on Cancer TNM Staging Systems on Esophageal Cancer Patients Treated With Chemoradiotherapy

Purpose: The new 7th edition of the American Joint Committee on Cancer TNM staging system is based on pathologic data from esophageal cancers treated by surgery alone. There is no information available on evaluation of the new staging system with regard to prognosis of patients treated with chemoradiotherapy (CRT). The objective of this study was to evaluate the prognostic impact of the new staging system on esophageal cancer patients treated with CRT. Methods and Materials: A retrospective review was performed on 301 consecutive esophageal squamous cell carcinoma patients treated with CRT. Comparisons were made of the prognostic impacts of the 6th and 7th staging systems and the prognostic impacts of stage and prognostic groups, which were newly defined in the 7th edition. Results: There were significant differences between Stages I and III (p < 0.01) according to both editions. However, the 7th edition poorly distinguishes the prognoses of Stages III and IV (p = 0.36 by multivariate analysis) in comparison to the 6th edition (p = 0.08 by multivariate analysis), although these differences were not significant. For all patients, T, M, and gender were independent prognostic factors by multivariate analysis (p < 0.05). For the Stage I and II prognostic groups, survival curves showed a stepwise decrease with increase in stage, except for Stage IIA. However, there were no significant differences seen between each prognostic stage. Conclusions: Our study indicates there are several problems with the 7th TNM staging system regarding prognostic factors in patients undergoing CRT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗