Assessing diagnostic tests once an optimal cutoff point has been selected.

1986 ◽  
Vol 32 (7) ◽  
pp. 1341-1346 ◽  
Author(s):  
K Linnet ◽  
E Brandt
Keyword(s):  
Test Performance ◽  
Diagnostic Tests ◽  
Statistical Tests ◽  
Cutoff Point ◽  
Standard Errors ◽  
Sample Sizes ◽  
Power Functions ◽  
Optimal Cutoff ◽  
Specificity And Sensitivity ◽  
Optimal Cutoff Point

Abstract The specificity and sensitivity of a quantitative diagnostic test depends on the chosen cutoff point. The common practice of selecting a cutoff point that maximizes the specificity plus the sensitivity, as judged from the observed test results, is studied here by simulation. Test performance is on average assessed too optimistically by this procedure--a phenomenon of importance when sample sizes are small. For example, the average positive bias is up to 15% of the test performance for sample sizes of 25. Furthermore, binomial calculated standard errors of specificity and sensitivity estimates are incorrect. A Monte Carlo statistical method--the "bootstrap procedure"--is applied to correct for bias and to estimate standard errors, including the standard error of the optimal cutoff point. Independent and paired comparisons of two diagnostic tests are also considered when optimal cutoff points have been selected. For this purpose, binomial statistical tests behave satisfactorily. Examples of power functions are presented.

scholarly journals An Optimal Cutoff Point of Expired-Air Carbon Monoxide Levels for Detecting Current Smoking: in the Case of a Japanese Male Population whose Smoking Prevalence was Sixty Percent

1998 ◽  
Vol 8 (3) ◽  
pp. 140-145 ◽  
Author(s):  
Takeo Nakayama ◽  
Akio Yamamoto ◽  
Takayoshi Ichimura ◽  
Nobuo Yoshiike ◽  
Tetsuji Yokoyama ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Smoking Prevalence ◽  
Cutoff Point ◽  
Male Population ◽  
Optimal Cutoff ◽  
Current Smoking ◽  
Japanese Male ◽  
Optimal Cutoff Point ◽  
Expired Air

Precision of sensitivity estimations in diagnostic test evaluations. Power functions for comparisons of sensitivities of two tests.

1985 ◽  
Vol 31 (4) ◽  
pp. 574-580 ◽  
Author(s):  
K Linnet
Keyword(s):  
Confidence Interval ◽  
Sample Size ◽  
Diagnostic Test ◽  
Diagnostic Tests ◽  
Sample Sizes ◽  
Power Functions ◽  
Gaussian Distributions ◽  
Sensitivity Estimate

Abstract The precision of estimates of the sensitivity of diagnostic tests is evaluated. "Sensitivity" is defined as the fraction of diseased subjects with test values exceeding the 0.975-fractile of the distribution of control values. An estimate of the sensitivity is subject to sample variation because of variation of both control observations and patient observations. If gaussian distributions are assumed, the 0.95-confidence interval for a sensitivity estimate is up to +/- 0.15 for a sample of 100 controls and 100 patients. For the same sample size, minimum differences of 0.08 to 0.32 of sensitivities of two tests are established as significant with a power of 0.90. For some published diagnostic test evaluations the median sample sizes for controls and patients were 63 and 33, respectively. I show that, to obtain a reasonable precision of sensitivity estimates and a reasonable power when two tests are being compared, the number of samples should in general be considerably larger.

scholarly journals The Prognostic Significance of Tumor Deposit Count for Colorectal Cancer Patients after Radical Surgery

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Kuo Zheng ◽  
Nanxin Zheng ◽  
Cheng Xin ◽  
Leqi Zhou ◽  
Ge Sun ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Prognostic Value ◽  
Validation Cohort ◽  
Cutoff Point ◽  
Disease Specific Survival ◽  
Optimal Cutoff ◽  
Training Cohort ◽  
Tumor Deposit ◽  
Optimal Cutoff Point ◽  
Disease Specific

Background. The prognostic value of tumor deposit (TD) count in colorectal cancer (CRC) patients has been rarely evaluated. This study is aimed at exploring the prognostic value of TD count and finding out the optimal cutoff point of TD count to differentiate the prognoses of TD-positive CRC patients. Method. Patients diagnosed with CRC from Surveillance, Epidemiology, and End Results (SEER) database from January 1, 2010, to December 31, 2012, were analyzed. X-tile program was used to identify the optimal cutoff point of TD count in training cohort, and a validation cohort was used to test this cutoff point after propensity score matching (PSM). Univariate and multivariate Cox proportional hazard models were used to assess the risk factors of survival. Results. X-tile plots identified 3 (P<0.001) as the optimal cutoff point of TD count to divide the patients of training cohort into high and low risk subsets in terms of disease-specific survival (DSS). This cutoff point was validated in validation cohort before and after PSM (P<0.001, P=0.002). More TD count, which was defined as more than 3, was validated as an independent risk prognostic factor in univariate and multivariate analysis (P<0.001). Conclusion. More TD count (TD count≥4) was significantly associated with poor disease-specific survival in CRC patients.

scholarly journals GW26-e2344 The optimal cutoff point of waist-to-hip ratio for Uyghur population aged over 35 years in Xinjiang

2015 ◽  
Vol 66 (16) ◽  
pp. C119
Author(s):  
Abudukeremu ◽  
Shuo Pan ◽  
Yining Yang ◽  
Xiang Ma ◽  
Xiaomei Li ◽  
...  
Keyword(s):  
Cutoff Point ◽  
Optimal Cutoff ◽  
Waist To Hip Ratio ◽  
Optimal Cutoff Point ◽  
Uyghur Population

scholarly journals Optimal Threshold of Homeostasis Model Assessment of Insulin Resistance to Identify Metabolic Syndrome in a Chinese Population Aged 45 Years or Younger

2022 ◽  
Vol 12 ◽  
Author(s):  
Szu-Yu Lin ◽  
Wen-Cheng Li ◽  
Ting-An Yang ◽  
Yi-Chuan Chen ◽  
Wei Yu ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Chinese Population ◽  
Cutoff Point ◽  
Optimal Threshold ◽  
Model Assessment ◽  
Homeostasis Model Assessment ◽  
Optimal Cutoff ◽  
Optimal Cutoff Point ◽  
Healthy Chinese

BackgroundMetabolic syndrome (MetS) is regarded as a major risk factor for diabetes mellitus and cardiovascular disease (CVD). The optimal threshold of the homeostasis model assessment of insulin resistance (HOMA-IR) has been established for predicting MetS in diverse populations and for different ages. This study assessed the serum HOMA-IR level in a healthy Chinese population aged ≤45 years to determine its relationship with metabolic abnormalities.MethodsCross-sectional study data were collected from health checkup records of Chinese adults aged ≥18 years between 2013 and 2016 at Xiamen Chang Gung Hospital. Participants completed a standardized questionnaire, which was followed by a health examination and blood sample collection. Exclusion criteria were as follows: history of known CVDs; liver, kidney, or endocrine diseases or recent acute illness; hypertension; hyperlipidemia; and pregnancy or lactation.ResultsThe clinical and laboratory characteristics of 5954 men and 4185 women were analyzed. Significant differences were observed in all assessed variables (all P &lt; 0.05). The optimal cutoff point of HOMA-IR for predicting MetS was 1.7 in men and 1.78 in women.ConclusionsWe aimed to determine the optimal cutoff point of HOMA-IR for predicting MetS in a healthy Chinese population aged ≤45 years. The findings of this study would provide an evidence-based threshold for evaluating metabolic syndromes and further implementing primary prevention programs, such as lifestyle changes in the target population.

Arthroscopic Assessment of Syndesmotic Instability in the Sagittal Plane in a Cadaveric Model

2019 ◽  
Vol 41 (2) ◽  
pp. 237-243 ◽  
Author(s):  
Bart Lubberts ◽  
Jafet Massri-Pugin ◽  
Daniel Guss ◽  
Jonathon C. Wolf ◽  
Rohan Bhimani ◽  
...  
Keyword(s):  
Sagittal Plane ◽  
Cutoff Point ◽  
Ligament Injury ◽  
Deltoid Ligament ◽  
Optimal Cutoff ◽  
Distal Fibula ◽  
Interosseous Ligament ◽  
Tibiofibular Ligament ◽  
Optimal Cutoff Point ◽  
Cadaveric Model

Background: Syndesmotic instability is multidirectional, occurring in the coronal, sagittal, and rotational planes. Despite the multitude of studies examining such instability in the coronal plane, other studies have highlighted that syndesmotic instability may instead be more evident in the sagittal plane. The aim of this study was to arthroscopically assess the degree of syndesmotic ligamentous injury necessary to precipitate fibular translation in the sagittal plane. Methods: Twenty-one above-knee cadaveric specimens underwent arthroscopic evaluation of the syndesmosis, first with all syndesmotic and ankle ligaments intact and subsequently with sequential sectioning of the anterior inferior tibiofibular ligament (AITFL), the interosseous ligament (IOL), the posterior inferior tibiofibular ligament (PITFL), and deltoid ligament (DL). In all scenarios, an anterior to posterior (AP) and a posterior to anterior (PA) fibular translation test were performed under a 100-N applied force. AP and PA sagittal plane translation of the distal fibula relative to the fixed tibial incisura was arthroscopically measured. Results: Compared with the intact ligamentous state, there was no difference in sagittal fibular translation when only 1 or 2 ligaments were transected. After transection of all the syndesmotic ligaments (AITFL, IOL, and PITFL) or after partial transection of the syndesmotic ligaments (AITFL, IOL) alongside the DL, fibular translation in the sagittal plane significantly increased as compared with the intact state ( P values ranging from .041 to <.001). The optimal cutoff point to distinguish stable from unstable injuries was equal to 2 mm of fibular translation for the total sum of AP and PA translation (sensitivity 77.5%; specificity 88.9%). Conclusion: Syndesmotic instability appears in the sagittal plane after injury to all 3 syndesmotic ligaments or after partial syndesmotic injury with concomitant deltoid ligament injury in this cadaveric model. The optimal cutoff point to arthroscopically distinguish stable from unstable injuries was 2 mm of total fibular translation. Clinical Relevance: These data can help surgeons arthroscopically distinguish between stable syndesmotic injuries and unstable ones that require syndesmotic stabilization.

The Optimal Cutoff Point of a Diagnostic Test

2011 ◽  
pp. 121-142
Author(s):  
Stefan Felder ◽  
Thomas Mayrhofer
Keyword(s):  
Diagnostic Test ◽  
Cutoff Point ◽  
Optimal Cutoff ◽  
Optimal Cutoff Point

scholarly journals Brief Pain Inventory–Facial minimum clinically important difference

2015 ◽  
Vol 122 (1) ◽  
pp. 180-190 ◽  
Author(s):  
Sukhmeet K. Sandhu ◽  
Casey H. Halpern ◽  
Venus Vakhshori ◽  
Keyvan Mirsaeedi-Farahani ◽  
John T. Farrar ◽  
...  
Keyword(s):  
Pain Intensity ◽  
Statistical Methods ◽  
Brief Pain Inventory ◽  
Minimum Clinically Important Difference ◽  
Change Score ◽  
Point Method ◽  
Cutoff Point ◽  
Optimal Cutoff ◽  
Clinically Important Difference ◽  
Optimal Cutoff Point

OBJECT Neurosurgeons are frequently the primary physicians measuring pain relief in patients with trigeminal neuralgia (TN). Unfortunately, the measurement of pain can be complex. The Brief Pain Inventory–Facial (BPI-Facial) is a reliable and validated multidimensional tool that consists of 18 questions. It measures 3 domains of pain: 1) pain intensity (worst and average pain intensity), 2) interference with general activities of daily living (ADL), and 3) face-specific pain interference. The objective of this paper is to determine the patient-reported minimum clinically important difference (MCID) using the BPI-Facial. METHODS The authors conducted a retrospective study of 234 patients with TN seen in a single neurosurgeon's office. Patients completed baseline and 1-month follow-up BPI-Facial questionnaires. The MCID was calculated using an anchor-based approach in which the defined anchor was the 7-point patient global impression of change (PGIC). Two statistical methods were employed: mean change score and optimal cutoff point. RESULTS Using the mean change score method, the investigators calculated the MCID for the 3 domains of the BPIFacial: 44% and 30% improvement in pain intensity at its worst and average, respectively, 54% improvement in interference with general ADL, and 63% improvement in interference with facial ADL. Using the optimal cutoff point method, they also calculated the MCID for the 3 domains of the BPI-Facial: 57% and 28% improvement in pain intensity at its worst and average, respectively, 75% improvement in interference with general ADL, and 62% improvement in interference with facial ADL. CONCLUSIONS The BPI-Facial is a multidimensional pain scale that measures 3 domains of pain. Although 2 statistical methods were used to calculate the MCID, the optimal cutoff point method was the superior one because it used data from the majority of subjects included in this study. A 57% improvement in pain intensity at its worst and a 28% improvement in pain intensity at its average were the MCIDs for patients with facial pain. A greater improvement was needed to achieve the MCID for interference with general and facial ADL. A 75% improvement in interference with general ADL and a 62% improvement in interference with facial ADL were needed to achieve an MCID. While pain intensity is easier to measure, pain's interference with ADL may be more important for patient outcomes when designing or evaluating interventions in the field of TN. The BPI-Facial is a useful instrument to measure changes in multidimensional aspects of pain in patients with TN.

Sign in / Sign up

Export Citation Format

Share Document