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Item Open Access A cloud-compatible bioinformatics pipeline for ultrarapid pathogen identification from next-generation sequencing of clinical samples.(Genome Res, 2014-07) Naccache, Samia N; Federman, Scot; Veeraraghavan, Narayanan; Zaharia, Matei; Lee, Deanna; Samayoa, Erik; Bouquet, Jerome; Greninger, Alexander L; Luk, Ka-Cheung; Enge, Barryett; Wadford, Debra A; Messenger, Sharon L; Genrich, Gillian L; Pellegrino, Kristen; Grard, Gilda; Leroy, Eric; Schneider, Bradley S; Fair, Joseph N; Martínez, Miguel A; Isa, Pavel; Crump, John A; DeRisi, Joseph L; Sittler, Taylor; Hackett, John; Miller, Steve; Chiu, Charles YUnbiased next-generation sequencing (NGS) approaches enable comprehensive pathogen detection in the clinical microbiology laboratory and have numerous applications for public health surveillance, outbreak investigation, and the diagnosis of infectious diseases. However, practical deployment of the technology is hindered by the bioinformatics challenge of analyzing results accurately and in a clinically relevant timeframe. Here we describe SURPI ("sequence-based ultrarapid pathogen identification"), a computational pipeline for pathogen identification from complex metagenomic NGS data generated from clinical samples, and demonstrate use of the pipeline in the analysis of 237 clinical samples comprising more than 1.1 billion sequences. Deployable on both cloud-based and standalone servers, SURPI leverages two state-of-the-art aligners for accelerated analyses, SNAP and RAPSearch, which are as accurate as existing bioinformatics tools but orders of magnitude faster in performance. In fast mode, SURPI detects viruses and bacteria by scanning data sets of 7-500 million reads in 11 min to 5 h, while in comprehensive mode, all known microorganisms are identified, followed by de novo assembly and protein homology searches for divergent viruses in 50 min to 16 h. SURPI has also directly contributed to real-time microbial diagnosis in acutely ill patients, underscoring its potential key role in the development of unbiased NGS-based clinical assays in infectious diseases that demand rapid turnaround times.Item Open Access A new predictive model for an improved respiratory isolation strategy in HIV-infected patients with PTB.(The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease, 2014-07) Carugati, M; Schiroli, C; Zanini, F; Vanoni, N; Galli, M; Adorni, F; Franzetti, FSetting
Luigi Sacco Hospital, Milan, Italy, 1 January 2000-31 December 2010.Objectives
To develop a predictive score for identifying human immunodeficiency virus (HIV) infected patients with pulmonary tuberculosis (PTB).Design
Retrospective study based on the medical charts of HIV-infected patients admitted consecutively on presumption of PTB. Patients with culture-positive TB were included in the TB group. Culture-negative subjects formed the non-TB group. Risk factors for PTB were identified and a predictive model was developed. The diagnostic test accuracy of the derived score and that of previously developed scores were analysed.Results
A total of 65 patients were included in the TB group and 505 subjects in the non-TB group. An eight-variable model (age, origin, alcohol use, respiratory rate, weight loss, haemoglobin, white blood cell count, typical chest X-ray) was derived. When compared with the different scores, this model showed the greatest area under the receiver operating characteristic curve (0.880). This score was the only one to present a negative likelihood ratio of <0.2, which is the threshold for giving strong diagnostic evidence against TB.Conclusions
This model may be useful in predicting PTB in HIV patients in low-endemic countries. A validation study is necessary.Item Open Access Alcohol and drug dependence symptom items as brief screeners for substance use disorders: results from the Clinical Trials Network.(Journal of psychiatric research, 2012-03) Wu, Li-Tzy; Blazer, Dan G; Woody, George E; Burchett, Bruce; Yang, Chongming; Pan, Jeng-Jong; Ling, WalterAIM:To address an urgent need for screening of substance use problems in medical settings, we examined substance-specific dependence criteria as potential brief screeners for the detection of patients with a substance use disorder (SUD). METHODS:The sample included 920 opioid-dependent adults who were recruited from outpatient treatment settings at 11 programs in 10 U.S. cities and who completed intake assessments of SUDs for a multisite study of the National Drug Abuse Treatment Clinical Trials Network (CTN003). Data were analyzed by factor analysis, item response theory (IRT), sensitivity, and specificity procedures. RESULTS:Across all substances (alcohol, amphetamines, cannabis, cocaine, sedatives), withdrawal was among the least prevalent symptoms, while taking large amounts and inability to cut down were among the most prevalent symptoms. Items closely related to the latent trait of a SUD showed good-to-high values of area under the receiver operating characteristic curve in identifying cases of a SUD; IRT-defined severe and less discriminative items exhibited low sensitivity in identifying cases of a SUD (withdrawal for all substances; time using for alcohol and sedatives; giving up activities for sedatives). CONCLUSIONS:Study results suggest that withdrawal and time using are much less reliable indicators for a SUD than taking larger amounts than intended and inability to cut down and that the latter two items should be studied further for consideration in developing a simplified tool for screening patients for SUDs in medical settings. These findings have implications for the use of common health indicators in electronic health records systems to improve patient care.Item Open Access An evaluation of patient self-testing competency of prothrombin time for managing anticoagulation: pre-randomization results of VA Cooperative Study #481--The Home INR Study (THINRS).(Journal of thrombosis and thrombolysis, 2010-10) Dolor, Rowena J; Ruybalid, R Lynne; Uyeda, Lauren; Edson, Robert G; Phibbs, Ciaran; Vertrees, Julia E; Shih, Mei-Chiung; Jacobson, Alan K; Matchar, David B; THINRS Site InvestigatorsPrior studies suggest patient self-testing (PST) of prothrombin time (PT) can improve the quality of anticoagulation (AC) and reduce complications (e.g., bleeding and thromboembolic events). "The Home INR Study" (THINRS) compared AC management with frequent PST using a home monitoring device to high-quality AC management (HQACM) with clinic-based monitoring on major health outcomes. A key clinical and policy question is whether and which patients can successfully use such devices. We report the results of Part 1 of THINRS in which patients and caregivers were evaluated for their ability to perform PST. Study-eligible patients (n = 3643) were trained to use the home monitoring device and evaluated after 2-4 weeks for PST competency. Information about demographics, medical history, warfarin use, medications, plus measures of numeracy, literacy, cognition, dexterity, and satisfaction with AC were collected. Approximately 80% (2931 of 3643) of patients trained on PST demonstrated competency; of these, 8% (238) required caregiver assistance. Testers who were not competent to perform PST had higher numbers of practice attempts, higher cuvette wastage, and were less able to perform a fingerstick or obtain blood for the cuvette in a timely fashion. Factors associated with failure to pass PST training included increased age, previous stroke history, poor cognition, and poor manual dexterity. A majority of patients were able to perform PST. Successful home monitoring of PT with a PST device required adequate levels of cognition and manual dexterity. Training a caregiver modestly increased the proportion of patients who can perform PST.Item Open Access Association of a peripheral blood metabolic profile with coronary artery disease and risk of subsequent cardiovascular events.(Circ Cardiovasc Genet, 2010-04) Shah, Svati H; Bain, James R; Muehlbauer, Michael J; Stevens, Robert D; Crosslin, David R; Haynes, Carol; Dungan, Jennifer; Newby, L Kristin; Hauser, Elizabeth R; Ginsburg, Geoffrey S; Newgard, Christopher B; Kraus, William EBACKGROUND: Molecular tools may provide insight into cardiovascular risk. We assessed whether metabolites discriminate coronary artery disease (CAD) and predict risk of cardiovascular events. METHODS AND RESULTS: We performed mass-spectrometry-based profiling of 69 metabolites in subjects from the CATHGEN biorepository. To evaluate discriminative capabilities of metabolites for CAD, 2 groups were profiled: 174 CAD cases and 174 sex/race-matched controls ("initial"), and 140 CAD cases and 140 controls ("replication"). To evaluate the capability of metabolites to predict cardiovascular events, cases were combined ("event" group); of these, 74 experienced death/myocardial infarction during follow-up. A third independent group was profiled ("event-replication" group; n=63 cases with cardiovascular events, 66 controls). Analysis included principal-components analysis, linear regression, and Cox proportional hazards. Two principal components analysis-derived factors were associated with CAD: 1 comprising branched-chain amino acid metabolites (factor 4, initial P=0.002, replication P=0.01), and 1 comprising urea cycle metabolites (factor 9, initial P=0.0004, replication P=0.01). In multivariable regression, these factors were independently associated with CAD in initial (factor 4, odds ratio [OR], 1.36; 95% CI, 1.06 to 1.74; P=0.02; factor 9, OR, 0.67; 95% CI, 0.52 to 0.87; P=0.003) and replication (factor 4, OR, 1.43; 95% CI, 1.07 to 1.91; P=0.02; factor 9, OR, 0.66; 95% CI, 0.48 to 0.91; P=0.01) groups. A factor composed of dicarboxylacylcarnitines predicted death/myocardial infarction (event group hazard ratio 2.17; 95% CI, 1.23 to 3.84; P=0.007) and was associated with cardiovascular events in the event-replication group (OR, 1.52; 95% CI, 1.08 to 2.14; P=0.01). CONCLUSIONS: Metabolite profiles are associated with CAD and subsequent cardiovascular events.Item Open Access Bayesian inference for genomic data integration reduces misclassification rate in predicting protein-protein interactions.(PLoS Comput Biol, 2011-07) Xing, Chuanhua; Dunson, David BProtein-protein interactions (PPIs) are essential to most fundamental cellular processes. There has been increasing interest in reconstructing PPIs networks. However, several critical difficulties exist in obtaining reliable predictions. Noticeably, false positive rates can be as high as >80%. Error correction from each generating source can be both time-consuming and inefficient due to the difficulty of covering the errors from multiple levels of data processing procedures within a single test. We propose a novel Bayesian integration method, deemed nonparametric Bayes ensemble learning (NBEL), to lower the misclassification rate (both false positives and negatives) through automatically up-weighting data sources that are most informative, while down-weighting less informative and biased sources. Extensive studies indicate that NBEL is significantly more robust than the classic naïve Bayes to unreliable, error-prone and contaminated data. On a large human data set our NBEL approach predicts many more PPIs than naïve Bayes. This suggests that previous studies may have large numbers of not only false positives but also false negatives. The validation on two human PPIs datasets having high quality supports our observations. Our experiments demonstrate that it is feasible to predict high-throughput PPIs computationally with substantially reduced false positives and false negatives. The ability of predicting large numbers of PPIs both reliably and automatically may inspire people to use computational approaches to correct data errors in general, and may speed up PPIs prediction with high quality. Such a reliable prediction may provide a solid platform to other studies such as protein functions prediction and roles of PPIs in disease susceptibility.Item Open Access Bone scan positivity in non-metastatic, castrate-resistant prostate cancer: external validation study.(International braz j urol : official journal of the Brazilian Society of Urology, 2020-01) Johnston, Ashley W; Longo, Thomas A; Davis, Leah Gerber; Zapata, Daniel; Freedland, Stephen J; Routh, Jonathan CIntroduction
Tables predicting the probability of a positive bone scan in men with non-metastatic, castrate-resistant prostate cancer have recently been reported. We performed an external validation study of these bone scan positivity tables.Materials and methods
We performed a retrospective cohort study of patients seen at a tertiary care medical center (1996-2012) to select patients with non-metastatic, castrate-resistant prostate cancer. Abstracted data included demographic, anthropometric, and disease-specific data such as patient race, BMI, PSA kinetics, and primary treatment. Primary outcome was metastasis on bone scan. Multivariable logistic regression was performed using generalized estimating equations to adjust for repeated measures. Risk table performance was assessed using ROC curves.Results
We identified 6.509 patients with prostate cancer who had received hormonal therapy with a post-hormonal therapy PSA ≥2ng/mL, 363 of whom had non-metastatic, castrate-resistant prostate cancer. Of these, 187 patients (356 bone scans) had calculable PSA kinetics and ≥1 bone scan. Median follow-up after castrate-resistant prostate cancer diagnosis was 32 months (IQR: 19-48). There were 227 (64%) negative and 129 (36%) positive bone scans. On multivariable analysis, higher PSA at castrate-resistant prostate cancer (4.67 vs. 4.4ng/mL, OR=0.57, P=0.02), shorter time from castrate-resistant prostate cancer to scan (7.9 vs. 14.6 months, OR=0.97, P=0.006) and higher PSA at scan (OR=2.91, P<0.0001) were significantly predictive of bone scan positivity. The AUC of the previously published risk tables for predicting scan positivity was 0.72.Conclusion
Previously published risk tables predicted bone scan positivity in men with non-metastatic, castrate-resistant prostate cancer with reasonable accuracy.Item Open Access Can psychological features predict antidepressant response to rTMS? A Discovery-Replication approach.(Psychological medicine, 2020-01) Krepel, Noralie; Rush, A John; Iseger, Tabitha A; Sack, Alexander T; Arns, MartijnBackground
Few studies focused on the relationship between psychological measures, major depressive disorder (MDD) and repetitive transcranial magnetic stimulation (rTMS) response. This study investigated several psychological measures as potential predictors for rTMS treatment response. Additionally, this study employed two approaches to evaluate the robustness of our findings by implementing immediate replication and full-sample exploration with strict p-thresholding.Methods
This study is an open-label, multi-site study with a total of 196 MDD patients. The sample was subdivided in a Discovery (60% of total sample, n = 119) and Replication sample (40% of total sample, n = 77). Patients were treated with right low frequency (1 Hz) or left high frequency (10 Hz) rTMS at the dorsolateral prefrontal cortex. Clinical variables [Beck Depression Inventory (BDI), Neuroticism, Extraversion, Openness Five-Factor Inventory, and Depression, Anxiety, and Stress Scale, and BDI subscales] were obtained at baseline, post-treatment, and at follow-up. Predictors were analyzed in terms of statistical association, robustness (independent replication), as well as for their clinical relevance [positive predictive value (PPV) and negative predictive value (NPV)].Results
Univariate analyses revealed that non-responders had higher baseline anhedonia scores. Anhedonia scores at baseline correlated negatively with total BDI percentage change over time. This finding was replicated. However, anhedonia scores showed to be marginally predictive of rTMS response, and neither PPV nor NPV reached the levels of clinical relevance.Conclusions
This study suggests that non-responders to rTMS treatment have higher baseline anhedonia scores. However, anhedonia was only marginally predictive of rTMS response. Since all other psychological measures did not show predictive value, it is concluded that psychological measures cannot be used as clinically relevant predictors to rTMS response in MDD.Item Open Access Comparative performance of multiview stereoscopic and mammographic display modalities for breast lesion detection.(2010) Webb, Lincoln JonPURPOSE: Mammography is known to be one of the most difficult radiographic exams to interpret. Mammography has important limitations, including the superposition of normal tissue that can obscure a mass, chance alignment of normal tissue to mimic a true lesion and the inability to derive volumetric information. It has been shown that stereomammography can overcome these deficiencies by showing that layers of normal tissue lay at different depths. If standard stereomammography (i.e., a single stereoscopic pair consisting of two projection images) can significantly improve lesion detection, how will multiview stereoscopy (MVS), where many projection images are used, compare to mammography? The aim of this study was to assess the relative performance of MVS compared to mammography for breast mass detection. METHODS: The MVS image sets consisted of the 25 raw projection images acquired over an arc of approximately 45 degrees using a Siemens prototype breast tomosynthesis system. The mammograms were acquired using a commercial Siemens FFDM system. The raw data were taken from both of these systems for 27 cases and realistic simulated mass lesions were added to duplicates of the 27 images at the same local contrast. The images with lesions (27 mammography and 27 MVS) and the images without lesions (27 mammography and 27 MVS) were then postprocessed to provide comparable and representative image appearance across the two modalities. All 108 image sets were shown to five full-time breast imaging radiologists in random order on a state-of-the-art stereoscopic display. The observers were asked to give a confidence rating for each image (0 for lesion definitely not present, 100 for lesion definitely present). The ratings were then compiled and processed using ROC and variance analysis. RESULTS: The mean AUC for the five observers was 0.614 +/- 0.055 for mammography and 0.778 +/- 0.052 for multiview stereoscopy. The difference of 0.164 +/- 0.065 was statistically significant with a p-value of 0.0148. CONCLUSIONS: The differences in the AUCs and the p-value suggest that multiview stereoscopy has a statistically significant advantage over mammography in the detection of simulated breast masses. This highlights the dominance of anatomical noise compared to quantum noise for breast mass detection. It also shows that significant lesion detection can be achieved with MVS without any of the artifacts associated with tomosynthesis.Item Open Access Comparisons of volumetric modulated arc therapy (VMAT) quality assurance (QA) systems: sensitivity analysis to machine errors.(Radiation Oncology (London, England), 2016-11-07) Liang, Bin; Liu, Bo; Zhou, Fugen; Yin, Fang-Fang; Wu, QiuwenIn volumetric modulated arc therapy (VMAT), gantry angles, dose rate and the MLC positions vary with the radiation delivery. The quality assurance (QA) system should be able to catch the planning and machine errors. The aim of this study was to investigate the sensitivity of three VMAT QA systems to machine errors.Several types of potential linac machine errors unique to VMAT delivery were simulated in sinusoidal function of gantry angle, including gantry angle itself, MLC position and linac output. Two commercial QA systems, ArcCheck and Delta4, and an in-house developed EPID technique were compared in this study. Fifteen full arcs from head and neck plans were selected and modified to include five magnitudes of each type of error, resulting in measurements and γ analyses of 240 arcs on each system. Both qualitative and quantitative comparisons were performed using receiver operating characteristic (ROC), γ pass rate gradient, and overlap histogram methods.In ROC analysis, the area under curve (AUC) represents the sensitivity and increases with the error magnitude. Using the criteria of 2 %/2 mm/2° (angle to agreement, ATA, only for EPID) and keeping AUC > 0.95, the minimum error detectable of ArcCheck, Delta4 and EPID are (2, 3, 3)° in gantry angle and (4, 2, 3) mm in MLC positions for the head and neck plans. No system is sensitive to the simulated output error, the AUC values were all below 0.70 even with 5 % output error. The γ gradient for gantry angle, MLC position and output errors are (-5.1, -2.6, -3.6)%/°, (-2.6, -7.1, -3.3)%/mm and (-0.2, -0.2, -0.3)%/% for ArcCheck, Delta4 and EPID, respectively. Therefore, these two analyses are consistent and support the same conclusion. The ATA parameter in EPID technique can be adjusted to tune its sensitivity.We found that ArcCheck is more sensitive to gantry angle error and Delta4 is more sensitive to MLC position error. All three systems are not sensitive to the simulated output error. With additional analysis parameter, the EPID technique can be tuned to have optimal sensitivity and is able to perform QA for full field size with highest resolution. In addition, ROC analysis avoids the choice of γ pass rate threshold and is more robust compared with other analysis methods.Item Open Access Cytokine profiles of preterm neonates with fungal and bacterial sepsis.(Pediatr Res, 2012-08) Sood, Beena G; Shankaran, Seetha; Schelonka, Robert L; Saha, Shampa; Benjamin, Danny K; Sánchez, Pablo J; Adams-Chapman, Ira; Stoll, Barbara J; Thorsen, Poul; Skogstrand, Kristin; Ehrenkranz, Richard A; Hougaard, David M; Goldberg, Ronald N; Tyson, Jon E; Das, Abhik; Higgins, Rosemary D; Carlo, Waldemar A; Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research NetworkBACKGROUND: Information on cytokine profiles in fungal sepsis (FS), an important cause of mortality in extremely low birthweight (ELBW) infants, is lacking. We hypothesized that cytokine profiles in the first 21 d of life in ELBW infants with FS differ from those with bacterial sepsis (BS) or no sepsis (NS). METHODS: In a secondary analysis of the National Institute of Child Health and Human Development Cytokine study, three groups were defined-FS (≥1 episode of FS), BS (≥1 episode of BS without FS), and NS. Association between 11 cytokines assayed in dried blood spots obtained on days 0-1, 3 ± 1, 7 ± 2, 14 ± 3, and 21 ± 3 and sepsis group was explored. RESULTS: Of 1,066 infants, 89 had FS and 368 had BS. As compared with BS, FS was more likely to be associated with lower birthweight, vaginal delivery, patent ductus arteriosus, postnatal steroids, multiple central lines, longer respiratory support and hospital stay, and higher mortality (P < 0.05). Analyses controlling for covariates showed significant group differences over time for interferon-γ (IFN-γ), interleukin (IL)-10, IL-18, transforming growth factor-β (TGF-β), and tumor necrosis factor-α (TNF-α) (P < 0.05). CONCLUSION: Significant differences in profiles for IFN-γ, IL-10, IL-18, TGF-β, and TNF-α in FS, BS, or NS in this hypothesis-generating secondary study require validation in rigorously designed prospective studies and may have implications for diagnosis and treatment.Item Open Access Development of a blood-based gene expression algorithm for assessment of obstructive coronary artery disease in non-diabetic patients.(BMC Med Genomics, 2011-03-28) Elashoff, Michael R; Wingrove, James A; Beineke, Philip; Daniels, Susan E; Tingley, Whittemore G; Rosenberg, Steven; Voros, Szilard; Kraus, William E; Ginsburg, Geoffrey S; Schwartz, Robert S; Ellis, Stephen G; Tahirkheli, Naheem; Waksman, Ron; McPherson, John; Lansky, Alexandra J; Topol, Eric JBACKGROUND: Alterations in gene expression in peripheral blood cells have been shown to be sensitive to the presence and extent of coronary artery disease (CAD). A non-invasive blood test that could reliably assess obstructive CAD likelihood would have diagnostic utility. RESULTS: Microarray analysis of RNA samples from a 195 patient Duke CATHGEN registry case:control cohort yielded 2,438 genes with significant CAD association (p < 0.05), and identified the clinical/demographic factors with the largest effects on gene expression as age, sex, and diabetic status. RT-PCR analysis of 88 CAD classifier genes confirmed that diabetic status was the largest clinical factor affecting CAD associated gene expression changes. A second microarray cohort analysis limited to non-diabetics from the multi-center PREDICT study (198 patients; 99 case: control pairs matched for age and sex) evaluated gene expression, clinical, and cell population predictors of CAD and yielded 5,935 CAD genes (p < 0.05) with an intersection of 655 genes with the CATHGEN results. Biological pathway (gene ontology and literature) and statistical analyses (hierarchical clustering and logistic regression) were used in combination to select 113 genes for RT-PCR analysis including CAD classifiers, cell-type specific markers, and normalization genes.RT-PCR analysis of these 113 genes in a PREDICT cohort of 640 non-diabetic subject samples was used for algorithm development. Gene expression correlations identified clusters of CAD classifier genes which were reduced to meta-genes using LASSO. The final classifier for assessment of obstructive CAD was derived by Ridge Regression and contained sex-specific age functions and 6 meta-gene terms, comprising 23 genes. This algorithm showed a cross-validated estimated AUC = 0.77 (95% CI 0.73-0.81) in ROC analysis. CONCLUSIONS: We have developed a whole blood classifier based on gene expression, age and sex for the assessment of obstructive CAD in non-diabetic patients from a combination of microarray and RT-PCR data derived from studies of patients clinically indicated for invasive angiography. CLINICAL TRIAL REGISTRATION INFORMATION: PREDICT, Personalized Risk Evaluation and Diagnosis in the Coronary Tree, http://www.clinicaltrials.gov, NCT00500617.Item Open Access Development of a preoperative predictive model for major complications following adult spinal deformity surgery.(Journal of neurosurgery. Spine, 2017-06) Scheer, Justin K; Smith, Justin S; Schwab, Frank; Lafage, Virginie; Shaffrey, Christopher I; Bess, Shay; Daniels, Alan H; Hart, Robert A; Protopsaltis, Themistocles S; Mundis, Gregory M; Sciubba, Daniel M; Ailon, Tamir; Burton, Douglas C; Klineberg, Eric; Ames, Christopher P; International Spine Study GroupOBJECTIVE The operative management of patients with adult spinal deformity (ASD) has a high complication rate and it remains unknown whether baseline patient characteristics and surgical variables can predict early complications (intraoperative and perioperative [within 6 weeks]). The development of an accurate preoperative predictive model can aid in patient counseling, shared decision making, and improved surgical planning. The purpose of this study was to develop a model based on baseline demographic, radiographic, and surgical factors that can predict if patients will sustain an intraoperative or perioperative major complication. METHODS This study was a retrospective analysis of a prospective, multicenter ASD database. The inclusion criteria were age ≥ 18 years and the presence of ASD. In total, 45 variables were used in the initial training of the model including demographic data, comorbidities, modifiable surgical variables, baseline health-related quality of life, and coronal and sagittal radiographic parameters. Patients were grouped as either having at least 1 major intraoperative or perioperative complication (COMP group) or not (NOCOMP group). An ensemble of decision trees was constructed utilizing the C5.0 algorithm with 5 different bootstrapped models. Internal validation was accomplished via a 70/30 data split for training and testing each model, respectively. Overall accuracy, the area under the receiver operating characteristic (AUROC) curve, and predictor importance were calculated. RESULTS Five hundred fifty-seven patients were included: 409 (73.4%) in the NOCOMP group, and 148 (26.6%) in the COMP group. The overall model accuracy was 87.6% correct with an AUROC curve of 0.89 indicating a very good model fit. Twenty variables were determined to be the top predictors (importance ≥ 0.90 as determined by the model) and included (in decreasing importance): age, leg pain, Oswestry Disability Index, number of decompression levels, number of interbody fusion levels, Physical Component Summary of the SF-36, Scoliosis Research Society (SRS)-Schwab coronal curve type, Charlson Comorbidity Index, SRS activity, T-1 pelvic angle, American Society of Anesthesiologists grade, presence of osteoporosis, pelvic tilt, sagittal vertical axis, primary versus revision surgery, SRS pain, SRS total, use of bone morphogenetic protein, use of iliac crest graft, and pelvic incidence-lumbar lordosis mismatch. CONCLUSIONS A successful model (87% accuracy, 0.89 AUROC curve) was built predicting major intraoperative or perioperative complications following ASD surgery. This model can provide the foundation toward improved education and point-of-care decision making for patients undergoing ASD surgery.Item Open Access Development of predictive models for all individual questions of SRS-22R after adult spinal deformity surgery: a step toward individualized medicine.(European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2019-09) Ames, Christopher P; Smith, Justin S; Pellisé, Ferran; Kelly, Michael; Gum, Jeffrey L; Alanay, Ahmet; Acaroğlu, Emre; Pérez-Grueso, Francisco Javier Sánchez; Kleinstück, Frank S; Obeid, Ibrahim; Vila-Casademunt, Alba; Shaffrey, Christopher I; Burton, Douglas C; Lafage, Virginie; Schwab, Frank J; Shaffrey, Christopher I; Bess, Shay; Serra-Burriel, Miquel; European Spine Study Group; International Spine Study GroupPurpose
Health-related quality of life (HRQL) instruments are essential in value-driven health care, but patients often have more specific, personal priorities when seeking surgical care. The Scoliosis Research Society-22R (SRS-22R), an HRQL instrument for spinal deformity, provides summary scores spanning several health domains, but these may be difficult for patients to utilize in planning their specific care goals. Our objective was to create preoperative predictive models for responses to individual SRS-22R questions at 1 and 2 years after adult spinal deformity (ASD) surgery to facilitate precision surgical care.Methods
Two prospective observational cohorts were queried for ASD patients with SRS-22R data at baseline and 1 and 2 years after surgery. In total, 150 covariates were used in training machine learning models, including demographics, surgical data and perioperative complications. Validation was accomplished via an 80%/20% data split for training and testing, respectively. Goodness of fit was measured using area under receiver operating characteristic (AUROC) curves.Results
In total, 561 patients met inclusion criteria. The AUROC ranged from 56.5 to 86.9%, reflecting successful fits for most questions. SRS-22R questions regarding pain, disability and social and labor function were the most accurately predicted. Models were less sensitive to questions regarding general satisfaction, depression/anxiety and appearance.Conclusions
To the best of our knowledge, this is the first study to explicitly model the prediction of individual answers to the SRS-22R questionnaire at 1 and 2 years after deformity surgery. The ability to predict individual question responses may prove useful in preoperative counseling in the age of individualized medicine. These slides can be retrieved under Electronic Supplementary Material.Item Open Access Diagnostic performance of short portable mental status questionnaire for screening dementia among patients attending cognitive assessment clinics in Singapore.(Annals of the Academy of Medicine, Singapore, 2013-07) Malhotra, Chetna; Chan, Angelique; Matchar, David; Seow, Dennis; Chuo, Adeline; Do, Young KyungIntroduction
The Short Portable Mental Status Questionnaire (SPMSQ) is a brief cognitive screening instrument, which is easy to use by a healthcare worker with little training. However, the validity of this instrument has not been established in Singapore. Thus, the primary aim of this study was to determine the diagnostic performance of SPMSQ for screening dementia among patients attending outpatient cognitive assessment clinics and to assess whether the appropriate cut-off score varies by patient's age and education. A secondary aim of the study was to map the SPMSQ scores with Mini-Mental State Examination (MMSE) scores.Materials and methods
SPMSQ and MMSE were administered by a trained interviewer to 127 patients visiting outpatient cognitive assessment clinics at the Singapore General Hospital, Changi General Hospital and Tan Tock Seng Hospital. The geriatricians at these clinics then diagnosed these patients with dementia or no dementia (reference standard). Sensitivity and specificity of SPMSQ with different cut-off points (number of errors) were calculated and compared to the reference standard using the Receiver Operator Characteristic (ROC) analysis. Correlation coefficient was also calculated between MMSE and SPMSQ scores.Results
Based on the ROC analysis and a balance of sensitivity and specificity, the appropriate cut-off for SPMSQ was found to be 5 or more errors (sensitivity 78%, specificity 75%). The cut-off varied by education, but not by patient's age. There was a high correlation between SPMSQ and MMSE scores (r = 0.814, P <0.0001).Conclusion
Despite the advantage of being a brief screening instrument for dementia, the use of SPMSQ is limited by its low sensitivity and specificity, especially among patients with less than 6 years of education.Item Open Access Differences in comorbidities on low back pain and low back related leg pain.(Pain practice : the official journal of World Institute of Pain, 2011-01) Goode, Adam; Cook, Chad; Brown, Christopher; Isaacs, Robert; Roman, Matthew; Richardson, WilliamObjective
Investigate the influence of external factors such as depression and BMI among subjects with primary severe low back pain (LBP) and low back related leg pain (LBLP).Background
The report of disability in patients with LBP may be significantly influenced by confounding and moderating variables. No similar studies have examined the influence of these factors on LBLP.Methods
This study included 1,448 consecutive subjects referred to a tertiary spine clinic. Unconditional binary logistic regression was used to determine the influence of comorbidities on the relationship between self-reported back and leg pain. A change in estimate formula was used to quantify this relationship.Results
Among those subjects with primary LBP the unadjusted odds ratio was 8.58 (95% CI 4.87, 15.10) and when adjusting for BMI, depression and smoking was 5.94 (95% CI 3.04, 11.60) resulting in a 36.7% change due to confounding by these comorbidities. Among those with primary LBLP, the unadjusted odds ratio was 4.49 (95% CI 2.78, 7.27) and when adjusting for BMI and depression was 4.60 (95% CI 2.58, 8.19) resulting in a 1.7% change due to confounding by these comorbidities.Conclusion
The disability statuses of the patients with primary LBP in this study were more significantly affected by comorbidities of BMI, depression and smoking than patients with report of LBLP. However, these comorbidities contribute little to the relationship of primary low back related leg pain and Oswestry scores ≥ 40.Item Open Access Evaluating brief screeners to discriminate between drug use disorders in a sample of treatment-seeking adults.(General hospital psychiatry, 2013-01) Wu, Li-Tzy; Swartz, Marvin S; Pan, Jeng-Jong; Burchett, Bruce; Mannelli, Paolo; Yang, Chongming; Blazer, Dan GOBJECTIVE:The objective was to identify a potential core set of brief screeners for the detection of individuals with a substance use disorder (SUD) in medical settings. METHOD:Data were from two multisite studies that evaluated stimulant use outcomes of an abstinence-based contingency management intervention as an addition to usual care (National Drug Abuse Treatment Clinical Trials Network trials 006-007). The sample comprised 847 substance-using adults who were recruited from 12 outpatient substance abuse treatment settings across the United States. Alcohol and drug use disorders were assessed by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Checklist. Data were analyzed by factor analysis, item response theory (IRT), sensitivity and specificity procedures. RESULTS:Comparatively prevalent symptoms of dependence, especially inability to cut down for all substances, showed high sensitivity for detecting an SUD (low rate of false negative). IRT-defined severe (infrequent) and low discriminative items, especially withdrawal for alcohol, cannabis and cocaine, had low sensitivity in identifying cases of an SUD. IRT-defined less severe (frequent) and high discriminative items, including inability to cut down or taking larger amounts than intended for all substances and withdrawal for amphetamines and opioids, showed good-to-high values of area under the receiver operating characteristic curve in classifying cases and noncases of an SUD. CONCLUSION:Findings suggest the feasibility of identifying psychometrically reliable substance dependence symptoms to develop a two-item screen for alcohol and drug disorders.Item Open Access Genetic variants in fanconi anemia pathway genes BRCA2 and FANCA predict melanoma survival.(The Journal of investigative dermatology, 2015-02) Yin, Jieyun; Liu, Hongliang; Liu, Zhensheng; Wang, Li-E; Chen, Wei V; Zhu, Dakai; Amos, Christopher I; Fang, Shenying; Lee, Jeffrey E; Wei, QingyiCutaneous melanoma (CM) is the most lethal skin cancer. The Fanconi anemia (FA) pathway involved in DNA crosslink repair may affect CM susceptibility and prognosis. Using data derived from published genome-wide association study, we comprehensively analyzed the associations of 2,339 common single-nucleotide polymorphisms (SNPs) in 14 autosomal FA genes with overall survival (OS) in 858 CM patients. By performing false-positive report probability corrections and stepwise Cox proportional hazards regression analyses, we identified significant associations between CM OS and four putatively functional SNPs: BRCA2 rs10492396 (AG vs. GG: adjusted hazard ratio (adjHR)=1.85, 95% confidence interval (CI)=1.16-2.95, P=0.010), rs206118 (CC vs. TT+TC: adjHR=2.44, 95% CI=1.27-4.67, P=0.007), rs3752447 (CC vs. TT+TC: adjHR=2.10, 95% CI=1.38-3.18, P=0.0005), and FANCA rs62068372 (TT vs. CC+CT: adjHR=1.85, 95% CI=1.27-2.69, P=0.001). Moreover, patients with an increasing number of unfavorable genotypes (NUG) of these loci had markedly reduced OS and melanoma-specific survival (MSS). The final model incorporating with NUG, tumor stage, and Breslow thickness showed an improved discriminatory ability to classify both 5-year OS and 5-year MSS. Additional investigations, preferably prospective studies, are needed to validate our findings.Item Open Access Genetic variants in RORA and DNMT1 associated with cutaneous melanoma survival.(International journal of cancer, 2018-06) Li, Bo; Wang, Yanru; Xu, Yinghui; Liu, Hongliang; Bloomer, Wendy; Zhu, Dakai; Amos, Christopher I; Fang, Shenying; Lee, Jeffrey E; Li, Xin; Han, Jiali; Wei, QingyiCutaneous melanoma (CM) is considered as a steroid hormone-related malignancy. However, few studies have evaluated the roles of genetic variants encoding steroid hormone receptor genes and their related regulators (SHR-related genes) in CM-specific survival (CMSS). Here, we performed a pathway-based analysis to evaluate genetic variants of 191 SHR-related genes in 858 CMSS patients using a dataset from a genome-wide association study (GWAS) from The University of Texas MD Anderson Cancer Center (MDACC), and then validated the results in an additional dataset of 409 patients from the Harvard GWAS. Using multivariate Cox proportional hazards regression analysis, we identified three-independent SNPs (RORA rs782917 G > A, RORA rs17204952 C > T and DNMT1 rs7253062 G > A) as predictors of CMSS, with a variant-allele attributed hazards ratio (HR) and 95% confidence interval of 1.62 (1.25-2.09), 1.60 (1.20-2.13) and 1.52 (1.20-1.94), respectively. Combined analysis of risk genotypes of these three SNPs revealed a decreased CMSS in a dose-response manner as the number of risk genotypes increased (ptrend < 0.001); however, no improvement in the prediction model was observed (area under the curve [AUC] = 79.6-80.8%, p = 0.656), when these risk genotypes were added to the model containing clinical variables. Our findings suggest that genetic variants of RORA and DNMT1 may be promising biomarkers for CMSS, but these results needed to be validated in future larger studies.Item Open Access Genetic variants of DNA repair genes predict the survival of patients with esophageal squamous cell cancer receiving platinum-based adjuvant chemotherapy.(Journal of translational medicine, 2016-05-31) Zhou, Fei; Zhu, Meiling; Wang, Mengyun; Qiu, Lixin; Cheng, Lei; Jia, Ming; Xiang, Jiaqing; Wei, QingyiAdjuvant chemotherapy in patients with resected esophageal squamous cell cancer (ESCC) remains controversial for its uncertain role in improving overall survival (OS). Nucleotide excision repair (NER) removes DNA-adducts in tumor cells induced by the platinum-based chemotherapy and thus may modulate efficacy of the treatment. The present study evaluated if single nucleotide polymorphisms (SNPs) of NER genes were prognostic biomarkers in ESCC patients treated with platinum-based adjuvant chemotherapy (PAC).The analysis included 572 patients, for whom six SNPs of NER genes [i.e., XPC (rs1870134 and rs2228001), ERCC2/XPD rs238406 and ERCC5/XPG (rs2094258, rs2296147 and rs873601)] were detected with the TaqMan assay. Kaplan-Meier analyses and Cox proportional hazards models were used to evaluate their associations with disease free survival (DFS) and OS of these ESCC patients receiving PAC. Receiving operating characteristic curve analysis was used to evaluate the role of the risk genotypes in the DFS and OS.We found that ERCC5/XPG rs2094258 and rs873601 and ERCC2/XPD rs238406 SNPs were independently associated with poorer DFS and OS of ESCC patients [ERCC5/XPG rs2094258: CT+TT vs. CC: adjusted hazards ratio (adjHR) = 1.68 and P = 0.012 for DFS; adjHR = 1.99 and P = 0.0001 for OS; ERCC5/XPG rs873601: GA+GG vs. AA: adjHR = 1.59 and P = 0.024 for DFS; adjHR = 1.91 and P = 0.0005 for OS; ERCC2/XPD rs238406: TT vs. GG+GT: adjHR = 1.43 and P = 0.020 for DFS; adjHR = 1.52 and P = 0.008 for OS]. These HRs increased as the number of risk genotypes increased in the combined analysis. The model combining the risk genotypes with clinical characteristics or the TNM stage system was better in predicting outcomes in ESCC patients with PAC.SNPs of ERCC2/XPD and ERCC5/XPG may independently and jointly predict survival of ESCC patients treated with PAC in this study population. Further validation in other study populations is warranted.