Simple methods for comparing two predictive values with incomplete data.

Statistical methods have been well developed for comparing the predictive values of two binary diagnostic tests under a paired design. However, existing methods do not make allowance for incomplete data. Although maximum likelihood based method can be used to deal with incomplete data, it requires iterative algorithm for implementation. A simple and easily implemented statistical method is therefore needed. Simple methods exist for comparing two sensitivities or specificities with incomplete data but such simple methods are not available for comparing two predictive values with incomplete data. In this paper, we propose two simple methods for comparing two predictive values with incomplete data. The test statistics derived by these two methods are simple to compute, only involving some minor modification of the existing weighted generalized score statistics with complete data. Simulation results demonstrate that the proposed methods are more efficient than the ad-hoc method that only uses the subjects wit complete data. As an illustration, the proposed methods are applied to an observational study comparing two non-invasive methods in detecting endometriosis.

Validity of luminometry and bacteriological tests for diagnosing intramammary infection at dry-off in dairy cows.

The objective of this cross-sectional study was to estimate the validity of laboratory culture, Petrifilm and Tri-Plate on-farm culture systems, as well as luminometry to correctly identify IMI at dry-off in dairy cows, considering all tests to be imperfect. From September 2020 until December 2021, we collected composite milk samples from cows before dry-off and divided them into 4 aliquots for luminometry, Petrifilm (aerobic count), Tri-Plate, and laboratory culture tests. We assessed multiple thresholds of relative light units (RLU) for luminometry, and we used thresholds of ≥100 cfu/mL for the laboratory culture, ≥50 cfu/mL for Petrifilm, and ≥1 cfu for Tri-Plate tests. We fitted Bayesian latent class analysis models to estimate the sensitivity (Se) and specificity (Sp) for each test to identify IMI, with 95% credibility interval (BCI). Using different prevalence measures (0.30, 0.50, and 0.70), we calculated the predictive values (PV) and misclassification cost terms (MCT) at different false negative-to-false-positive ratios (FN:FP). A total of 333 cows were enrolled in the study from one commercial Holstein herd. The validity of the luminometry was poor for all thresholds, with an Se of 0.51 (95% BCI = 0.43-0.59) and Sp of 0.38 (95% BCI = 0.26-0.50) when using a threshold of ≥150 RLU. The laboratory culture had an Se of 0.93 (95% BCI = 0.85-0.98) and Sp of 0.69 (95% BCI = 0.49-0.89); the Petrifilm had an Se of 0.91 (95% BCI = 0.80-0.98) and Sp of 0.71 (95% BCI = 0.51-0.90); and the Tri-Plate had an Se of 0.65 (95% BCI = 0.53-0.82) and Sp of 0.85 (95% BCI = 0.66-0.97). Bacteriological tests had good PV, with comparable positive PV for all 3 tests, but lower negative PV for the Tri-Plate compared with the laboratory culture and the Petrifilm. For a prevalence of IMI of 0.30, all 3 tests had similar MCT, but for prevalence of 0.50 and 0.70, the Tri-Plate had higher MCT in scenarios where leaving a cow with IMI untreated is considered to have greater detrimental effects than treating a healthy cow (i.e., FN:FP of 3:1). Our results showed that the bacteriological tests have adequate validity to diagnose IMI at dry-off, but luminometry does not. We concluded that although luminometry is not useful to identify IMI at dry-off, the Petrifilm and Tri-Plate tests performed similarly to laboratory culture, depending on the prevalence and importance of the FP and FN results.

Number of positive lymph nodes and lymph node ratio predict recurrence and survival in hypopharyngeal cancer based on SEER database and validation of real-world data.

PURPOSE: This study investigated the impacts of the number of positive lymph nodes (NPLN) and lymph node ratio (LN ratio) for patients with hypopharyngeal squamous cell carcinoma (HPSCC) based on SEER database, which were validated in the real-world data of China. METHODS: A total of 520 patients from SEER database were analyzed. Then 195 patients with pathologically stage III or IV HPSCC in our center were retrospectively studied. RESULTS: In the SEER database, NPLN ≥ 3 was found in 36.9% of patients. Multivariate analysis revealed that LN ratio ≥ 0.138 was significant with poorer overall survival (OS) (hazard ratio [HR] = 1.525, p = 0.001) and cancer-specific survival (CSS) (HR = 1.697, p < 0.001), so was the NPLN ≥ 3 (HR = 1.388, p = 0.013; HR = 1.479, p = 0.008). Patients with NPLN ≥ 3 were found in 103 (52.8%) in our center. Multivariate analysis confirmed a significant association regarding OS (p = 0.005) or CSS (p = 0.003) between patients with LN ratio ≥ 0.138 or not. In addition, disease recurrence rate differed significantly between the patients with NPLN ≥ 3 (27.2%) and NPLN < 3 (14.1%, p = 0.026). Moreover, postoperative chemoradiotherapy (CCRT) was significantly associated with better prognosis in patients with NPLN ≥ 3. CONCLUSION: In the SEER database, NPLN ≥ 3 and LN ratio ≥ 0.138 were independent poor prognostic factors for patients with HPSCC. Whereas identifying worldwide cut-off values for LN ratio is difficult and surgeon-dependent. In our cohort, adjuvant CCRT was beneficial for OS in patients with NPLN ≥ 3.

The Headphone and Loudspeaker Test-Part II: A comprehensive method for playback device screening in Internet experiments.

HALT (The Headphone and Loudspeaker Test) Part II is a continuation of HALT Part I. The main goals of this study (HALT Part II) were (a) to develop screening tests and strategies to discriminate headphones from loudspeakers, (b) to come up with a methodological approach to combine more than two screening tests, and (c) to estimate data quality and required sample sizes for the application of screening tests. Screening Tests A and B were developed based on psychoacoustic effects. In a first laboratory study (N = 40), the two tests were evaluated with four different playback devices (circumaural and intra-aural headphones; external and laptop loudspeakers). In a final step, the two screening tests A and B and a previously established test C were validated in an Internet-based study (N = 211). Test B showed the best single-test performance (sensitivity = 80.0%, specificity = 83.2%, AUC = .844). Following an epidemiological approach, the headphone prevalence (17.67%) was determined to calculate positive and negative predictive values. For a user-oriented, parameter-based selection of suitable screening tests and the simple application of screening strategies, an online tool was programmed. HALT Part II is assumed to be a reliable procedure for planning and executing screenings to detect headphone and loudspeaker playback. Our methodological approach can be used as a generic technique for optimizing the application of any screening tests in psychological research. HALT Part I and II complement each other to form a comprehensive overall concept to control for playback conditions in Internet experiments.

Validation of diagnosis codes for chorioamnionitis in medical encounter data, 2013-2018.

PURPOSE: Chorioamnionitis refers to intrauterine infection/inflammation that can be diagnosed clinically or from laboratory testing. This study aimed to validate chorioamnionitis International Classification of Diseases (ICD) codes using reference standards for clinical and histologic cases. METHODS: Department of Defense Birth and Infant Health Research program data identified a cohort of live deliveries at two United States military hospitals from 2013 to 2018. Deliveries were screened for chorioamnionitis using ICD codes from maternal delivery records; a sample of screen positive and negative deliveries was selected for chart review. Primary analyses validated deliveries using a reference standard for clinical chorioamnionitis; secondary analyses employed a reference standard that also included histologic cases, but were limited by temporal differences in availability of laboratory data. Sensitivity, specificity, and positive (PPV) and negative (NPV) predictive values were calculated with 95% confidence intervals (CIs). RESULTS: Overall, 1857 deliveries (465 screen positive, 1392 screen negative) were eligible for analysis and 336 met the reference standard for clinical chorioamnionitis, yielding a PPV of 0.68 (95% CI 0.63, 0.72) and sensitivity of 0.76 (95% CI 0.72, 0.81). In secondary analyses, 390 deliveries met the reference standard for clinical or histologic chorioamnionitis, resulting in an overall PPV of 0.75 (95% CI 0.71, 0.79); in 2018, when more laboratory results were available, the PPV was 0.91 (95% CI 0.84, 0.97). NPV and specificity were ≥0.97 across reference standards. CONCLUSIONS: Chorioamnionitis ICD codes exhibited moderate correlation with clinical disease, suggesting challenges in using medical encounter data to isolate clinical cases from those only identified through laboratory testing.

Joint comparison of the predictive values of multiple binary diagnostic tests: an extension of McNemar's test.

Positive and negative predictive values are important measures of the clinical accuracy of a diagnostic test. Various test statistics have been proposed to compare positive predictive values or negative predictive values of two binary diagnostic tests separately. However, such separate comparisons do not present a complete picture of the relative accuracy of the two diagnostic tests. In this paper, we propose an extension of McNemar's test for the joint comparison of predictive values of multiple diagnostic tests. The proposed extended McNemar's test is intuitive and simple to compute, only involving cell counts of discordant pairs from multiple 2×2 tables. Furthermore, we also propose a re-formulation of an existing Wald test statistic so that it can be implemented more easily than its original form. Simulations demonstrate that the proposed extended McNemar's test statistic preserves type one error much better than the existing Wald test statistic. Thus, we believe that the proposed extended McNemar's test statistic is the preferred statistic to simultaneously compare the predictive values of multiple binary diagnostic tests.

Evaluation of test-day milk somatic cell count to predict intramammary infection in late lactation grazing dairy cows.

Use of selective dry cow antimicrobial therapy requires to precisely differentiate cows with an intramammary infection (IMI) from uninfected cows close to drying-off to enable treatment allocation. Milk somatic cell count (SCC) is an indicator of an inflammatory response in the mammary gland and is usually associated with IMI. However, SCC can also be influenced by cow-level variables such as milk yield, lactation number and stage of lactation. In recent years, predictive algorithms have been developed to differentiate cows with IMI from cows without IMI based on SCC data. The objective of this observational study was to explore the association between SCC and subclinical IMI, taking cognizance of cow-level predictors on Irish seasonal spring calving, pasture-based systems. Additionally, the optimal test-day SCC cut-point (maximized sensitivity and specificity) for IMI diagnosis was determined. A total of 2,074 cows, across 21 spring calving dairy herds with an average monthly milk weighted bulk tank SCC of ≤200,000 cells/mL were enrolled in the study. Quarter-level milk sampling was carried out on all cows in late lactation (interquartile range = 240-261 d in milk) for bacteriological culturing. Bacteriological results were used to define cows with IMI, when ≥1 quarter sample resulted in bacterial growth. Cow-level test-day SCC records were provided by the herd owners. The ability of the average, maximum and last test-day SCC to predict infection were compared using receiver operator curves. Predictive logistic regression models tested included parity (primiparous or multiparous), yield at last test-day and a standardized count of high SCC test-days. In total, 18.7% of cows were classified as having an IMI, with first parity cows having a higher proportion of IMI (29.3%) compared with multiparous cows (16.1%). Staphylococcus aureus accounted for the majority of these infections. The last test-day SCC was the best predictor of infection with the highest area under the curve. The inclusions of parity, yield at last test-day, and a standardized count of high SCC test-days as predictors did not significantly improve the ability of last test-day SCC to predict IMI. The cut-point for last test-day SCC which maximized sensitivity and specificity was 64,975 cells/mL. This study indicates that in Irish seasonal pasture-based dairy herds, with low bulk tank SCC control programs, the last test-day SCC (interquartile range days in milk = 221-240) is the best predictor of IMI in late lactation.

What is the diagnostic accuracy of neutrophil to lymphocyte ratio and monocyte to lymphocyte ratio in detecting acute periprosthetic joint infections? A gender-specific analysis.

PURPOSE: The accurate and timely diagnosis of periprosthetic joint infection (PJI) is critical for guiding optimal treatment management and success, highlighting the requirement of readily available inexpensive serum biomarkers to increase the diagnostic accuracy for PJI. Many studies have investigated the diagnostic accuracy of neutrophil to lymphocyte ratio (NLR) and monocyte to lymphocyte ratio (MLR). However, there is a lack of existing literature regarding optimal thresholds for acute PJI. The purpose of this study was to reveal the most appropriate cut-off values for MLR and NLR in detecting acute PJI with a gender specific analysis. METHODS: Patients were classified as having an acute PJI if they met the International Consensus Meeting (ICM) 2018 modified criteria. Patients who had a negative clinical and diagnostic workup for a PJI and the presence of erythema on the index surgical area were included in the erysipelas group (control group). Data obtained from all patients included age, sex, body mass index (BMI), Charlson Comorbidity Index (CCI), procedure type (THA or TKA), serum C-reactive protein (CRP), and blood studies at the admission and culture results were retrieved from the electronic medical record. RESULTS: ROC curve analysis was used to determine the gender-specific optimal threshold values for CRP, NLR, and MLR. Comparing the sensitivities and specificities of NLR and MLR at the identified best thresholds in males and females, the study found similar sensitivities of NLR in males and females with 0.84 and 0.84, respectively. On the other hand, an MLR of 0.67 or more reported a notably higher specificity in male patients [0.90 (95% CI 0.75-0.96) versus 0.70 (95% CI 0.56-0.80)]. CONCLUSION: NLR and MLR represent commonly ordered, low-cost, simple, and readily available complete cell count laboratory values and should be used as adjunct tests with reasonable diagnostic accuracy in detecting acute PJIs. Moreover, with its excellent specificity and PPV, MLR could provide valuable insight in diagnosing acute PJI, particularly in male patients. LEVEL OF EVIDENCE: Level III Retrospective Cohort analysis.

Positive Predictive Values of Anaphylaxis Diagnosis in Claims Data: A Multi-Institutional Study in Taiwan.

Real-world data sources can facilitate essential understanding of the epidemiological features of anaphylaxis. However, the accuracy of case-identifying definitions based on diagnosis codes for anaphylaxis in healthcare databases remains understudied. We conducted a cross-sectional study analyzing claims data from the largest multi-institutional healthcare system in Taiwan during 2017-2021. We included patients with incident anaphylaxis identified by either ICD-10-CM codes for anaphylaxis (Group 1) or ICD-10-CM codes for severe allergic or drug adverse events and additional modifier codes for acute allergy events (Group 2). We randomly selected 20% of the cases to determine the positive predictive value (PPV) of anaphylaxis case-identifying definitions in Groups 1 and 2 after review of electronic medical records by two physicians. From the original cohort (n = 2,176), we randomly selected 433 patients with either a diagnosis of anaphylaxis (Group 1), or a diagnosis of severe allergic and drug adverse events with additional modifier codes for acute allergy events (Group 2). In Group 1, we judged 135 / 170 patients as true anaphylaxis cases, giving a PPV of 79.4% (95% CI: 73.3-85.5). In Group 2, we judged 47 / 263 patients as true anaphylaxis cases, giving a PPV of 17.9% (95% CI: 13.3-22.5). In conclusion, acceptable PPVs were observed when anaphylaxis cases were identified by ICD-10-CM codes for anaphylaxis, but not by ICD-10-CM codes for severe allergic or drug adverse event with additional modifier codes for acute allergy events. Our multi-institutional findings could serve as a fundamental reference for further studies of anaphylaxis based on real-world healthcare databases.

Measurement of anti-suprabasin antibodies, multiple cytokines and chemokines as potential predictive biomarkers for neuropsychiatric systemic lupus erythematosus.

Neuropsychiatric systemic lupus erythematosus (NPSLE) varies in presentation and is one of the leading causes of morbidity and mortality among patients with SLE. This study determined the most critical serum biomarkers for the development of NPSLE as they may have clinical utility prior to the onset of neuropsychiatric symptoms. We retrospectively analyzed 35 NPSLE patients, 34 SLE patients, 20 viral meningitis (VM) patients, and 16 relapsing-remitting multiple sclerosis (MS) patients. We measured anti-suprabasin antibodies concentrations in serum by using Luciferase immunoprecipitation system (LIPS) assay. The serum concentrations of cytokines/chemokines were measured by using multiplex bead-based assay. We found serum FGF-2 level was significantly higher in the NPSLE group compared to the SLE group and the healthy control group. The anti-suprabasin antibody relative concentration (SRC) has high positive predictive values for the development of NPSLE. The most essential biomarkers are VEGF, anti-suprabasin antibodies, sCD40L, IL-10, GRO, MDC, IL-8, IL-9, TNF-α, MIP-1α.

Potential clinical utility of liquid biopsy in early-stage non-small cell lung cancer.

BACKGROUND: Liquid biopsy has been widely researched for early diagnosis, prognostication and disease monitoring in lung cancer, but there is a need to investigate its clinical utility for early-stage non-small cell lung cancer (NSCLC). METHODS: We performed a meta-analysis and systematic review to evaluate diagnostic and prognostic values of liquid biopsy for early-stage NSCLC, regarding the common biomarkers, circulating tumor cells, circulating tumor DNA (ctDNA), methylation signatures, and microRNAs. Cochrane Library, PubMed, EMBASE databases, ClinicalTrials.gov, and reference lists were searched for eligible studies since inception to 17 May 2022. Sensitivity, specificity and area under the curve (AUC) were assessed for diagnostic values. Hazard ratio (HR) with a 95% confidence interval (CI) was extracted from the recurrence-free survival (RFS) and overall survival (OS) plots for prognostic analysis. Also, potential predictive values and treatment response evaluation were further investigated. RESULTS: In this meta-analysis, there were 34 studies eligible for diagnostic assessment and 21 for prognostic analysis. The estimated diagnostic values of biomarkers for early-stage NSCLC with AUCs ranged from 0.84 to 0.87. The factors TNM stage I, T1 stage, N0 stage, adenocarcinoma, young age, and nonsmoking contributed to a lower tumor burden, with a median cell-free DNA concentration of 8.64 ng/ml. For prognostic analysis, the presence of molecular residual disease (MRD) detection was a strong predictor of disease relapse (RFS, HR, 4.95; 95% CI, 3.06-8.02; p < 0.001) and inferior OS (HR, 3.93; 95% CI, 1.97-7.83; p < 0.001), with average lead time of 179 ± 74 days between molecular recurrence and radiographic progression. Predictive values analysis showed adjuvant therapy significantly benefited the RFS of MRD + patients (HR, 0.27; p < 0.001), while an opposite tendency was detected for MRD - patients (HR, 1.51; p = 0.19). For treatment response evaluation, a strong correlation between pathological response and ctDNA clearance was detected, and both were associated with longer survival after neoadjuvant therapy. CONCLUSIONS: In conclusion, our study indicated liquid biopsy could reliably facilitate more precision and effective management of early-stage NSCLC. Improvement of liquid biopsy techniques and detection approaches and platforms is still needed, and higher-quality trials are required to provide more rigorous evidence prior to their routine clinical application.

Laboratory and clinical predictors of focal involvement and bacteremia in brucellosis.

Early diagnosis of organ involvement and bacteremia in brucellosis increases treatment success and may prevent poor clinical outcomes. This study aimed to investigate the predictors of focal involvement and bacteremia in patients with brucellosis. A total of 139 brucellosis patients aged 16 years and older were included in the study. Patients with and without organ involvement and bacteremic and non-bacteremic patients were compared separately. Low back pain, lymphadenomegaly, absence of fever on admission, ESR, AST, and neutrophil-lymphocyte ratio (NLR) were predictors of focal involvement (OR: 2.604; 3.167; 7.224; 1.039; 1.032; 1.738, respectively). The AUC value of ESR was 0.669 (0.573-0.765, p = 0.002) with the cutoff point > 30 mm/h (sensitivity 89.74% and specificity 37.00%) in predicting focal involvement in patients with brucellosis. Myalgia and headache (OR: 2.970; 2692) were defined as clinical predictors of Brucella bacteremia. Focal involvement should be considered in patients with brucellosis in the absence of myalgia and fever, presence of low back pain, and sedimentation > 30 mm/h. Brucella bacteremia should be considered regardless of fever, especially in patients with myalgia and headache in endemic areas.

Statistics in diagnostic medicine.

This tutorial gives an introduction into statistical methods for diagnostic medicine. The validity of a diagnostic test can be assessed using sensitivity and specificity which are defined for a binary diagnostic test with known reference or gold standard. As an example we use Procalcitonin with a cut off value ≥ 0.5 g/L as a test and Sepsis-2 criteria as a reference standard for the diagnosis of sepsis. Next likelihood ratios are introduced which combine the information given by sensitivity and specificity. For these measures the construction of confidence intervals is demonstrated. Then, we introduce predictive values using Bayes' theorem. Predictive values are sometimes difficult to communicate. This can be improved using natural frequencies which are applied to our example. Procalcitonin is actually a continuous biomarker, hence we introduce the use of receiver operator curves (ROC) and the area under the curve (AUC). Finally we discuss sample size estimation for diagnostic studies. In order to show how to apply these concepts in practice we explain how to use the freely available software R.

Retrospective analysis of radiographic signs in feline pleural effusions to predict disease aetiology.

BACKGROUND: The objectives of the study were to determine the prevalence of underlying conditions causing pleural effusion in cats and to calculate the positive predictive values, negative predictive values, sensitivity and specificity of radiographic signs to predict aetiology of the pleural fluid. METHODS: Data from 148 cats with pleural effusion and diagnosed with known aetiologies were retrospectively analysed. Sixty one cats had thoracic radiographs evaluated by consensus through pre-defined radiographic signs by two radiologists blinded to the diagnoses. RESULTS: Congestive heart failure (53.4%) was the most common diagnosis, followed by neoplasia (20.3%), pyothorax (10.8%), idiopathic chylous effusion (5.4%), feline infectious peritonitis (1.4%) and "other" or cats with multiple diagnoses (total 8.8%). Cats with an enlarged cardiac silhouette had a high positive predictive value of congestive heart failure (90%). Mediastinal masses (100%)and pulmonary masses (100%) were highly predictive of neoplastic disease. Pulmonary nodules (50%) were poorly predictive of neoplastic disease. The remainder of the radiographic variables were not informative predictors of underlying disease. CONCLUSIONS: In our sample of cats, congestive heart failure was the most common cause of pleural effusion. Radiographically enlarged cardiac silhouette and presence of a mediastinal mass may be useful predictors of aetiology, however there are limitations to the use of radiography alone as a diagnostic tool.

Assess predictive values of a binary diagnostic test under a nested case-control design.

Predictive values of a binary diagnostic test are often evaluated under a random sample design. When the disease is rare, however, such a design might not be as efficient as a nested case-control design where the cases are oversampled from a large existing cohort. Under a nested case-control design, direct proportion estimators of predictive values are biased because cases are oversampled. Consistent estimates of predictive values can be easily obtained by inverse probability weighting (IPW) method. The only difficulty with these IPW estimators has been the absence of expressions for their variances. To fill this gap, in the current paper, we obtain the asymptotic variance formulas for the IPW estimators of predictive values. Unlike their counterparts from weighted logistic regression, our variance formulas take into account the variance of the estimated weights in the IPW estimators of predictive values. We further use the proposed variance formulas to examine the gain in efficiency under a nested case-control design compared with a simple random sampling design. Our results clearly show that when the disease is rare, a nested case-control design can achieve a substantial amount of variance reduction by oversampling cases, compared with a random sample design. Finally, we compare via simulation the accuracy of the proposed variance formulas with the existing methods and illustrate the proposed method by a real data example evaluating the accuracy of D-dimer test.

Problems associated with mass border testing of COVID-19.

We evaluated the yield of exit screening for SARS-Cov-2 performed in order for travellers to meet entry requirements to Sweden. Among 472 people screened, no infectious case of COVID-19 was detected, while two previously known cases were redetected after having already completed isolation. Our data suggest that depending on the epidemiological situation in the area of departure, border screening can lead to very low positive predictive values and very high costs per relevant case detected.

Use of diagnostic likelihood ratio of outcome to evaluate misclassification bias in the planning of database studies.

BACKGROUND: The diagnostic likelihood ratio (DLR) and its utility are well-known in the field of medical diagnostic testing. However, its use has been limited in the context of an outcome validation study. We considered that wider recognition of the utility of DLR would enhance the practices surrounding database studies. This is particularly timely and important since the use of healthcare-related databases for pharmacoepidemiology research has greatly expanded in recent years. In this paper, we aimed to advance the use of DLR, focusing on the planning of a new database study. METHODS: Theoretical frameworks were developed for an outcome validation study and a comparative cohort database study; these two were combined to form the overall relationship. Graphical presentations based on these relationships were used to examine the implications of validation study results on the planning of a database study. Additionally, novel uses of graphical presentations were explored using some examples. RESULTS: Positive DLR was identified as a pivotal parameter that connects the expected positive-predictive value (PPV) with the disease prevalence in the planned database study, where the positive DLR is equal to sensitivity/(1-specificity). Moreover, positive DLR emerged as a pivotal parameter that links the expected risk ratio with the disease risk of the control group in the planned database study. In one example, graphical presentations based on these relationships provided a transparent and informative summary of multiple validation study results. In another example, the potential use of a graphical presentation was demonstrated in selecting a range of positive DLR values that best represented the relevant validation studies. CONCLUSIONS: Inclusion of the DLR in the results section of a validation study would benefit potential users of the study results. Furthermore, investigators planning a database study can utilize the DLR to their benefit. Wider recognition of the full utility of the DLR in the context of a validation study would contribute meaningfully to the promotion of good practice in planning, conducting, analyzing, and interpreting database studies.

One in Four Dies of Cancer. Questions About the Epidemiology of Malignant Tumours.

Cancer is the second leading cause of death globally. Malignant tumours are responsible for about 9.6 million deaths in 2018 (Ritchie H (2019) How many people in the world die from cancer? https://ourworldindata.org/how-many-people-in-the-world-die-from-cancer ). Worldwide, about 1 in 6 deaths is due to cancer. This confronts researches with the question of their origin and doctors with treatment options. It is common sense that great efforts should be done in order to reduce the number of cancer-specific deaths. In recent years, in lots of countries a variety of cancer screening programs have been developed, investigated and improved. The basic idea of this approach seems to be quite simple: Tumours will be detected at a very early stage when patients do not yet feel clinical symptoms. Thus, using an appropriate therapy, progression of the disease can be prevented and, concerning a whole population, disease-specific mortality should be reduced. Actually, after the introduction of screening programs, an increasing number of new cancer cases can be observed associated with an apparent reduction of the case fatality rate (i.e. the proportion of deaths due to cancer). Partly, the increasing number of cancers may be explained by the fact that people have a higher life expectancy. Under this aspect, the decreased case fatality rate could be considered as a success which may be attributed to screening efforts. However, there is still insufficient evidence affirming benefits of screening programs for crucial outcomes, i.e. all-cause mortality. In this narrative review, the phenomenon that probabilities and risks are rather often interpreted in an inadmissible way will be described. Furthermore, conceptual issues and inconsistencies between evidence and opinion about screening will be explored.

Cytokeratin 18 can help predict liver fibrosis in HCV infected patients with type 2 diabetes mellitus.

BACKGROUND: To investigate the predictive values of cytokeratin 18 for liver fibrosis in hepatitis C virus (HCV) infected patients with type 2 diabetes mellitus (T2DM). METHODS: 252 HCV-infected patients with T2DM between January 2012 and August 2017 were retrospectively reviewed. Pearson/spearman correlation analysis was used to detect the correlation in the entire cohort. Multivariate linear regression was used to identify independent predictors and logistic regression was for establishing models. Combination models that incorporated CK18 and other methods (i.e. transient elastography, aspartate transaminase-to-platelet ratio index (APRI) and fibrosis-4 index (FIB-4)] were developed in a training cohort of 132 patients. Performance of models was evaluated through discrimination ability and clinical benefits. An internal validation was conducted in 120 consecutive patients. RESULTS: CK18 was found significantly associated with fibrosis scores (r = 0.452, P < .001). CK18 and albumin were confirmed as independent predictors for fibrosis. For predicting significant fibrosis in the validation cohort, the observed AUC values of APRI + CK18 (AUC 0.83) and FIB-4 + CK18 (AUC 0.84) were higher than those of APRI (AUC 0.61) and FIB-4 (AUC 0.65). For predicting advanced fibrosis and cirrhosis, the AUC values of FIB-4 + CK18 (AUC 0.74 and 0.77, respectively) were significantly higher than those of FIB-4 (AUC 0.61 of both). Decision curve analysis confirmed the more clinical benefits can be provided by being combined with CK18. CONCLUSIONS: CK18 is an independent predictor of liver fibrosis for HCV-infected patients with T2DM. Noninvasive methods incorporate CK18 and other biomarker indices can have better performance for diagnosing fibrosis and help clinical decision-making.

The aetiology of pharyngotonsillitis in primary health care: a prospective observational study.

BACKGROUND: Few studies on pharyngotonsillitis have examined the clinical presentation of different aetiologies where pathogens have been detected using molecular methods. We aimed to assess how well clinical signs and symptoms can predict (1) the presence or absence of a broad range of viruses and bacteria, and (2) reconsultations for a sore throat or a complication. METHODS: In this descriptive observational prospective study in primary health care 220 patients aged 15-45 with suspected pharyngotonsillitis were sampled from nose, throat and blood and screened for 20 bacteria and viruses using polymerase chain reaction (PCR), culture and serology. Odds ratios (OR) and predictive values with 95% confidence intervals (CI) were used to show association between microbiological findings and clinical signs and symptoms. Patients were followed up after 3 months by reviewing electronic medical records. RESULTS: Both cough and coryza were more common in patients with only viruses (67%) than in patients with only bacteria (21%) (p < 0.001), whereas tonsillar coating was more common in patients with only bacteria (53%) than in patients with only viruses (29%) (p = 0.006). Tonsillar coating (adjusted OR 6.0; 95% CI 2.5-14) and a lack of cough (adjusted OR 3.5; 95% CI 1.5-8.0) were significantly associated with Streptococcus pyogenes (group A streptococci; GAS) and with any bacterial finding. A Centor score of 3-4 had a positive predictive value of 49% (95% CI 42-57) for GAS and 66% (95% CI 57-74) for any bacterial findings. The use of rapid antigen detection test for GAS increased the positive predictive value for this group to 93%. CONCLUSIONS: Signs and symptoms, both single and combined, were insufficient to rule in GAS or other pathogens. However, both cough and coryza were useful to rule out GAS. The results support the clinical approach of restricting rapid antigen detection testing to patients with 3-4 Centor criteria. The low carriage rate of bacteria among asymptomatic controls implied that most detections in patients represented a true infection.