Performance of Distress Thermometer and Associated Factors of Psychological Distress among Chinese Cancer Patients
ABSTRACT: Objective We aimed to examine the performance of the distress thermometer (DT) and identify the prevalence and risk factors associated with psychological distress (PD) in heterogeneous cancer patients. Methods This cross-sectional study enrolled 1496 heterogeneous cancer patients from the inpatient and outpatient departments. Receiver operating characteristic analysis (ROC) of DT was evaluated against the Hospital Anxiety and Depression Scale-Total (HADS-T ?15). An area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and clinical utility index were calculated. Multiple binary logistic regression was used to identify the factors associated with PD. Results Referring to ROC analysis, DT showed good discriminating accuracy (AUC?=?0.88). A cutoff score of 4 was established, and it yielded sensitivity (0.81), specificity (0.88), PPV (0.87), NPV (0.82), and clinical utility indexes (screening utility?=?0.71 and case-finding utility?=?0.73). 46.5% of our participants was distressed. Lower education levels (odd ratio (OR)?=?1.39), advanced stage (OR?=?1.85), active disease status (OR?=?1.82), lack of exercise (OR?=?3.03), diagnosis known (OR?=?0.64), emotional problems (OR?=?3.54), and physical problems (OR?=?8.62) were the predictive factors for PD. Conclusion DT with a cutoff score (?4) is a comprehensive, appropriate, and practical initial screener for PD in cancer patients. Predicting factors should be considered together for effective management of PD in such population.
Project description:Background:Many biomarkers for diagnosis of acute appendicitis in children have been reported, however, the results are still controversial. We assessed the accuracy of neutrophil-lymphocyte ratio (NLR) for diagnosis of acute appendicitis and discriminating simple and complicated appendicitis in children. Methods:We included 121 patients with acute appendicitis and 49 children with intussusception as controls who were admitted at our hospital from 2013 to 2017. White blood count (WBC), neutrophil, and NLR were compared between groups. Results:Neutrophil and NLR were significantly higher in the acute appendicitis group than control (76.17?±?14.41 vs. 62.43?±?15.9%, p=<0.0001; and 8.44?±?6.63 vs. 3.38?±?2.84, p=<0.0001, respectively), while WBC, neutrophil, and NLR were significantly greater in complicated than simple appendicitis (15.86?±?6.48 vs. 12.64?±?6.27?×?103/?L, p?=?0,008; 82.64?±?8.41 vs. 68.99?±?16.23%, p=<0.0001; and 11.32?±?6.87 vs. 5.25?±?4.65, p=<0.0001, respectively). The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under the receiver operating characteristic (ROC) curve, and cutoff point of NLR for diagnosis of acute appendicitis were 83.5%, 57.7%, 81.4%, 61.2%, 0.764, and 2.87, respectively; whereas the sensitivity, specificity, PPV, NPV, area under the ROC curve, and cutoff point of NLR for differentiating complicated and simple appendicitis were 84.6%, 56.5%, 35.5%, 92.9%, 0.790, and 6.59, respectively. Conclusion:NLR shows a high accuracy for diagnosis of acute appendicitis and distinguishing a complicated appendicitis from the simple one.
Project description:BACKGROUND: In the absence of overt clinical signs of Johne's Disease (JD), laboratory based tests have largely been limited to organism detection via faecal culture or PCR and serological tests for antibody reactivity. In this study we describe the application of quantitative faecal PCR for the detection of Mycobacterium avium subsp. paratuberculosis (MAP) in New Zealand farmed deer to quantify the bacterial load in cervine faecal samples as an adjunct to an existing serodiagnostic test (Paralisa™) tailored for JD diagnosis in deer. As ELISA has potential as a cheap, high throughput screening test for JD, an attempt was made to assess the sensitivity, specificity and positive/negative predictive (PPV/NPV) values of Paralisa™ for estimating levels of faecal shedding of MAP as a basis for JD management in deer. RESULTS: Correlations were made between diagnostic tests (ELISA, qPCR, culture and histopathology) to establish the precision and predictive values of individual tests. The findings from this study suggest there is strong correlation between bacterial shedding, as determined by faecal qPCR, with both culture (r = 0.9325) and histopathological lesion severity scoring (r = 0.7345). Correlation between faecal shedding and ELISA reactivity in deer was weaker with values of r = 0.4325 and r = 0.4006 for Johnin and Protoplasmic antigens, respectively. At an ELISA Unit (EU) cutoff of >50 (Johnin antigen) the PPV of Paralisa™ for significant faecal shedding in deer (>104 organisms/g) was moderate (0.55) while the NPV was higher (0.89). At an EU cutoff of ? 150, the PPV for shedding >105 organisms/g rose to 0.88, with a corresponding NPV of 0.85. CONCLUSIONS: The evidence available from this study suggests that Paralisa™ used at a cutoff of 50EU could be used to screen deer herds for MAP infection with sequential qPCR testing used to cull all Paralisa™ positive animals that exhibit significant MAP faecal shedding.
Project description:BACKGROUND:Intervertebral instability is a relatively common finding among patients with chronic neck pain after whiplash trauma. Videofluoroscopy (VF) of the cervical spine is a potentially sensitive diagnostic tool for evaluating instability, as it offers the ability to examine relative intervertebral movement over time, and across the entire continuum of voluntary movement of the patient. At the present time, there are no studies of the diagnostic accuracy of VF for discriminating between injured and uninjured populations. METHODS:Symptomatic (injured) study subjects were recruited from consecutive patients with chronic (>6 weeks) post-whiplash pain presenting to medical and chiropractic offices equipped with VF facilities. Asymptomatic (uninjured) volunteers were recruited from family and friends of patients. An ethical review and oversight were provided by the Spinal Injury Foundation, Broomfield, CO. Three statistical models were utilized to assess the sensitivity, specificity, positive and negative predictive values (PPV and NPV) of positive VF findings to correctly discriminate between injured and uninjured subjects. RESULTS:A total of 196 subjects (119 injured, 77 uninjured) were included in the study. All three statistical models demonstrated high levels of sensitivity and specificity (i.e., receiver operating characteristic (ROC) values of 0.71 to 0.95), however, the model with the greatest practical clinical utility was based on the number of abnormal VF findings. For 2+ abnormal VF findings, the ROC was 0.88 (93% sensitivity, 79% specificity) and the PPV and NPV were both 88%. The highest PPV (1.0) was observed with 4+ abnormal findings. CONCLUSIONS:Videofluoroscopic examination of the cervical spine provides a high degree of diagnostic accuracy for the identification of vertebral instability in patients with chronic pain stemming from whiplash trauma.
Project description:Background:Postoperative day 1-drains amylase (POD1-DA) values are commonly used to predict the risk of pancreatic fistula (PF) after pancreaticoduodenectomy (PD). Perioperative inflammatory biomarkers have been associated to higher risk of complications in different oncological surgeries. Aim of this study was to investigate the utility of the combination of preoperative inflammatory biomarkers (PIBs) with POD1-DA levels in predicting grade C PF. Materials and methods:From a prospective collected database of 317 consecutive pancreaticoduodenectomies, data regarding POD1-DA levels and PIBs as neutrophil-to-lymphocyte ratio (NRL), derived neutrophil-to-lymphocyte ratio (dNRL), platelet-to-lymphocyte ratio (PLR) were analyzed in 227 cases. P-values <0.05 were considered statistically significant. Receiver operating characteristic (ROC) curves defined the optimal thresholds for biomarkers and drains amylase values and their accuracy to predict PF. Furthermore, the Positive Predictive Value (PPV) was computed to evaluate the probability to develop PF combining PIBs and drains amylase values. Combination of drains amylase and different PIBs cut-offs were used to evaluate the risk of grade C PF. Results:A POD1-DA level of 351 U/L significantly predicted PF (sensitivity 82.7%, specificity 76%, AUC 0.836; p < 0.001) with a PPV of 76.5% and a NPV of 82.6%.POD1-DA levels ?807 U/L significantly predicted grade C PF (sensitivity 72.7%, specificity 64.4%, AUC 0.676; p = 0.004) with a PPV of 17.8% and a NPV of 95.6%.Notably, this last PPV increased from 17.8% to 89% when PIBs, at different cut-offs, were combined with POD1-DA at the value ? 807 U/L. Conclusion:PIBs significantly improve POD1-DA ability in predicting grade C PF after PD.
Project description:Background:Disease prevalence is rarely explicitly considered in the early stages of the development of novel prognostic tests. Rather, researchers use the area under the receiver operating characteristic (AUROC) as the key metric to gauge and report predictive performance ability. Because this statistic does not account for disease prevalence, proposed tests may not appropriately address clinical requirements. This ultimately impedes the translation of prognostic tests into clinical practice. Methods:A method to express positive- and/or negative predictive value criteria (PPV, NPV) within the ROC space is presented. Equations are derived for so-called equi-PPV (and equi-NPV) lines. Herewith it is possible, for any given prevalence, to plot a series of sensitivity-specificity pairs which meet a specified PPV (or NPV) criterion onto the ROC space.This concept is introduced by firstly reviewing the well-established "mechanics", strengths and limitations of the ROC analysis in the context of developing prognostic models. Then, the use of PPV (and/or) NPV criteria to augment the ROC analysis is elaborated.Additionally, an interactive web tool was also created to enable people to explore the dynamics of lines of equi-predictive value in function of prevalence. The web tool also allows to gauge what ROC curve shapes best meet specific positive and/or negative predictive value criteria (http://d4ta.link/ppvnpv/). Results:To illustrate the merits and implications of this concept, an example on the prediction of pre-eclampsia risk in low-risk nulliparous pregnancies is elaborated. Conclusions:In risk stratification, the clinical usefulness of a prognostic test can be expressed in positive- and negative predictive value criteria; the development of novel prognostic tests will be facilitated by the possibility to co-visualise such criteria together with ROC curves. To achieve clinically meaningful risk stratification, the development of separate tests to meet either a pre-specified positive value (rule-in) or a negative predictive value (rule-out) criteria should be considered: the characteristics of successful rule-in and rule-out tests may markedly differ.
Project description:Binary test outcomes typically result from dichotomizing a continuous test variable, observable or latent. The effect of the threshold for test positivity on test sensitivity and specificity has been studied extensively in receiver operating characteristic (ROC) analysis. However, considerably less attention has been given to the study of the effect of the positivity threshold on the predictive value of a test. In this paper we present methods for the joint study of the positive (PPV) and negative predictive values (NPV) of diagnostic tests. We define the predictive receiver operating characteristic (PROC) curve that consists of all possible pairs of PPV and NPV as the threshold for test positivity varies. Unlike the simple trade-off between sensitivity and specificity exhibited in the ROC curve, the PROC curve displays what is often a complex interplay between PPV and NPV as the positivity threshold changes. We study the monotonicity and other geometric properties of the PROC curve and propose summary measures for the predictive performance of tests. We also formulate and discuss regression models for the estimation of the effects of covariates.
Project description:INTRODUCTION:Automated electronic sniffers may be useful for early detection of acute respiratory distress syndrome (ARDS) for institution of treatment or clinical trial screening. METHODS:In a prospective cohort of 2929 critically ill patients, we retrospectively applied published sniffer algorithms for automated detection of acute lung injury to assess their utility in diagnosis of ARDS in the first 4 ICU days. Radiographic full-text reports were searched for "edema" OR ("bilateral" AND "infiltrate") and a more detailed algorithm for descriptions consistent with ARDS. Patients were flagged as possible ARDS if a radiograph met search criteria and had a PaO2/FiO2 or SpO2/FiO2 of 300 or 315, respectively. Test characteristics of the electronic sniffers and clinical suspicion of ARDS were compared to a gold standard of 2-physician adjudicated ARDS. RESULTS:Thirty percent of 2841 patients included in the analysis had gold standard diagnosis of ARDS. The simpler algorithm had sensitivity for ARDS of 78.9%, specificity of 52%, positive predictive value (PPV) of 41%, and negative predictive value (NPV) of 85.3% over the 4-day study period. The more detailed algorithm had sensitivity of 88.2%, specificity of 55.4%, PPV of 45.6%, and NPV of 91.7%. Both algorithms were more sensitive but less specific than clinician suspicion, which had sensitivity of 40.7%, specificity of 94.8%, PPV of 78.2%, and NPV of 77.7%. CONCLUSIONS:Published electronic sniffer algorithms for ARDS may be useful automated screening tools for ARDS and improve on clinical recognition, but they are limited to screening rather than diagnosis because their specificity is poor.
Project description:BACKGROUND:Chronic obstructive pulmonary disease (COPD) is a major public health problem and cause of mortality worldwide. However, COPD in the early stage is usually not recognized and diagnosed. It is necessary to establish a risk model to predict COPD development. METHODS:A total of 441 COPD patients and 192 control subjects were recruited, and 101 single-nucleotide polymorphisms (SNPs) were determined using the MassArray assay. With 5 clinical features as well as SNPs, 6 predictive models were established and evaluated in the training set and test set by the confusion matrix AU-ROC, AU-PRC, sensitivity (recall), specificity, accuracy, F1 score, MCC, PPV (precision) and NPV. The selected features were ranked. RESULTS:Nine SNPs were significantly associated with COPD. Among them, 6 SNPs (rs1007052, OR?=?1.671, P?=?0.010; rs2910164, OR?=?1.416, P?<?0.037; rs473892, OR?=?1.473, P?<?0.044; rs161976, OR?=?1.594, P?<?0.044; rs159497, OR?=?1.445, P?<?0.045; and rs9296092, OR?=?1.832, P?<?0.045) were risk factors for COPD, while 3 SNPs (rs8192288, OR?=?0.593, P?<?0.015; rs20541, OR?=?0.669, P?<?0.018; and rs12922394, OR?=?0.651, P?<?0.022) were protective factors for COPD development. In the training set, KNN, LR, SVM, DT and XGboost obtained AU-ROC values above 0.82 and AU-PRC values above 0.92. Among these models, XGboost obtained the highest AU-ROC (0.94), AU-PRC (0.97), accuracy (0.91), precision (0.95), F1 score (0.94), MCC (0.77) and specificity (0.85), while MLP obtained the highest sensitivity (recall) (0.99) and NPV (0.87). In the validation set, KNN, LR and XGboost obtained AU-ROC and AU-PRC values above 0.80 and 0.85, respectively. KNN had the highest precision (0.82), both KNN and LR obtained the same highest accuracy (0.81), and KNN and LR had the same highest F1 score (0.86). Both DT and MLP obtained sensitivity (recall) and NPV values above 0.94 and 0.84, respectively. In the feature importance analyses, we identified that AQCI, age, and BMI had the greatest impact on the predictive abilities of the models, while SNPs, sex and smoking were less important. CONCLUSIONS:The KNN, LR and XGboost models showed excellent overall predictive power, and the use of machine learning tools combining both clinical and SNP features was suitable for predicting the risk of COPD development.
Project description:The aim of the study was to evaluate the effect of laparoscopic-based score combined with a multiple disciplinary team (MDT) for predicting optimal cytoreduction and perform personalized surgical treatment in recurrent ovarian cancer (ROC).The study is a single-center, prospective investigation. From March 2013 to May 2015, the consecutive treated patients with platinum-sensitive ROC were collected in Yangpu Hospital. The appropriated patients were enrolled into the study to perform the laparoscopic-based PIV (predictive index value) score assessment with an MDT for predicting optimal cytoreduction. The PIV cutoff value was confirmed to be 8. Patients of PIV <8 received laparoscopic/laparotomy secondary surgery following chemotherapy, and the ones with PIV ?8 did chemotherapy alone. Sensitivity, specificity, positive predicted value (PPV), negative predicted value (NPV), and overall accuracy for each range of PIV score were calculated. All recruited patients participated in follow-up observation. Overall survival was recorded.In total, 58 eligible ROC patients received laparoscopy assessment. Forty-one patients of PIV <8 received secondary cytoreductive surgeries. Twenty-three (23/41 56.1%) attained optimal cytoreduction. However, 8 of 23 achieved completed cytoreduction. Also, 17 patients of PIV ?8 underwent chemotherapy alone. Sensitivity, specificity, PPV, NPV, and overall accuracy for PIV ?8 were 60%, 100%, 100%, 25%, and 64.7%, respectively. Overall survival in patients performing optimal cytoreduction was significantly higher than in those undergoing suboptimal cytoreduction or chemotherapy alone (45.9?±?2.5 vs 36.7?±?4.3 months, P?=?.047; 45.9?±?2.5 vs 35.8?±?3.4 months, P?=?.027).Laparoscopic-based score assessment plus MDT helps to identify the appropriate patients to perform optimal secondary cytoreduction and provide a personalized surgical approach in management of ROC.
Project description:Fabry disease (FD) patients may suffer from objective cognitive impairment (OCI). This study assessed the accuracy of the Mini Mental State Examination (MMSE) to screen for OCI in FD patients. Presence or absence of OCI was established using a neuropsychological test battery. For different MMSE cutoffs sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and clinical utility index (CUI) to identify OCI were calculated. Eighty-one patients were included (mean age 44.5?±?14.3, 35% men, 74% classical phenotype) of which 13 patients (16%) had OCI. The median MMSE score was 29 (range: 25-30). MMSE cutoffs ?28 and??29 had the highest sensitivity and specificity, with higher specificity reached at cutoff ?28 (sensitivity: .46, specificity: .73) and higher sensitivity at cutoff ?29 (sensitivity: .92, specificity: .40). PPV was low for both cutoffs (PPV ?28: .25, PPV ?29: .23) resulting in a low positive CUI (case finding ability). The results of our study indicate that the MMSE does not accurately screen for OCI in FD, with poor sensitivity-specificity trade-off at all cutoffs. The low PPV shows that the majority of FD patients that score below the cutoffs do not suffer from OCI. Administering the MMSE as a screening test will lead to unnecessary referrals for neuropsychological testing, which is time consuming and burdensome. Screening tools designed to accurately detect mild (executive) impairment might prove more appropriate to screen for OCI in FD.