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PubMed2026

A stratified urine-based molecular diagnostic and prognostic model for non-muscle-invasive bladder cancer management.

BACKGROUND: Non-muscle-invasive bladder cancer (NMIBC) is characterized by a high recurrence rate requiring lifelong cystoscopic surveillance. Existing urine-based molecular assays mainly rely on mutations or methylation, which fail to capture large-scale genomic instability. Copy number variation (CNV) profiling offers complementary information on tumor evolution and aggressiveness, but its application in urinary diagnosis remains limited. We aimed to integrate CNV and DNA methylation signals from urinary DNA to establish a noninvasive and biologically informed stratified diagnostic model for NMIBC recurrence surveillance and risk stratification. METHODS: Urine samples were prospectively collected from 91 patients (75 evaluable) between June 2021 and August 2023. Shallow whole-genome sequencing (sWGS) was used to detect CNVs at chromosomal arm and focal gene levels, while ONECUT2 promoter methylation was quantified by qPCR. Diagnostic and prognostic performance was evaluated by ROC analysis, Kaplan-Meier survival, and stratified recurrence assessment. RESULTS: We evaluated a stratified diagnostic model combining CNV and ONECUT2 methylation testing in a cohort of 79 patients. CNV analysis alone showed high specificity (0.923) for NMIBC diagnosis. A combined model, using CNV as an initial screen followed by ONECUT2 methylation testing in CNV-positive cases, achieved a sensitivity of 0.783, specificity of 0.981, and a negative predictive value (NPV) of 0.911. This approach reduced the number of required ONECUT2 tests by 35% and identified a high proportion of true-negative patients (98.1%), which may help reduce unnecessary cystoscopy procedures. The model also demonstrated significant prognostic value, with the molecularly defined high-risk group showing significantly shorter recurrence-free survival (RFS) than the low-risk group (median RFS: 4.33 months vs. not reached; p&#x2009;<&#x2009;0.001). Additional, in patients with initially negative cystoscopy after urine sample collection, the model demonstrated a predictive accuracy of 0.922 for recurrence, with molecular positivity observed a median of 9.6 months prior to clinical diagnosis. CONCLUSIONS: Integrating CNV and DNA methylation profiling from urinary DNA provides a powerful and noninvasive molecular framework for NMIBC surveillance. By combining early epigenetic changes with genomic instability signals, this approach enhances recurrence risk assessment and enables earlier detection compared with conventional cystoscopy. It offers a practical route toward personalized and adaptive post-treatment monitoring of NMIBC. TRIAL REGISTRATION: NCT04994197.

Humans↗
PubMed2005

GEMS: a system for automated cancer diagnosis and biomarker discovery from microarray gene expression data.

The success of treatment of patients with cancer depends on establishing an accurate diagnosis. To this end, we have built a system called GEMS (gene expression model selector) for the automated development and evaluation of high-quality cancer diagnostic models and biomarker discovery from microarray gene expression data. In order to determine and equip the system with the best performing diagnostic methodologies in this domain, we first conducted a comprehensive evaluation of classification algorithms using 11 cancer microarray datasets. In this paper we present a preliminary evaluation of the system with five new datasets. The performance of the models produced automatically by GEMS is comparable or better than the results obtained by human analysts. Additionally, we performed a cross-dataset evaluation of the system. This involved using a dataset to build a diagnostic model and to estimate its future performance, then applying this model and evaluating its performance on a different dataset. We found that models produced by GEMS indeed perform well in independent samples and, furthermore, the cross-validation performance estimates output by the system approximate well the error obtained by the independent validation. GEMS is freely available for download for non-commercial use from http://www.gems-system.org.

Algorithms↗
PubMed1997

A Weibull regression model with gamma frailties for multivariate survival data.

Frequently in the analysis of survival data, survival times within the same group are correlated due to unobserved co-variates. One way these co-variates can be included in the model is as frailties. These frailty random block effects generate dependency between the survival times of the individuals which are conditionally independent given the frailty. Using a conditional proportional hazards model, in conjunction with the frailty, a whole new family of models is introduced. By considering a gamma frailty model, often the issue is to find an appropriate model for the baseline hazard function. In this paper a flexible baseline hazard model based on a correlated prior process is proposed and is compared with a standard Weibull model. Several model diagnostics methods are developed and model comparison is made using recently developed Bayesian model selection criteria. The above methodologies are applied to the McGilchrist and Aisbett (1991) kidney infection data and the analysis is performed using Markov Chain Monte Carlo methods.

Bayes Theorem↗
PubMed1989

Application of fuzzy set theory to biochemical processes--a new model for problem diagnosis.

Fuzzy set theory provides a helpful basis for study of model building in biochemical processes. A new approach to the field of problem diagnosis, based on fuzzy set theory, has been devised. This paper describes a practical diagnostic model for the problem of contamination in an industrial antibiotic production process. The results of theoretical analysis and on-site testing show that this approach can also be used as a prototype for modeling similar diagnostic problems.

Anti-Bacterial Agents↗
PubMed2006

Diagnostic architectural and dynamic features at breast MR imaging: multicenter study.

PURPOSE: To prospectively determine the prevalence and predictive value of three-dimensional (3D) and dynamic breast magnetic resonance (MR) imaging and contrast material kinetic features alone and as part of predictive diagnostic models. MATERIALS AND METHODS: The study protocol was approved by the institutional review board or ethics committees of all participating institutions, and informed consent was obtained from all participants. Although study data collection was performed before HIPAA went into effect, standards that would be compliant with HIPAA were adhered to. Data from the International Breast MR Consortium trial 6883 were used in the analysis. Women underwent 3D (minimum spatial resolution, 0.7 x 1.4 x 3 mm; minimal temporal resolution, 4 minutes) and dynamic two-dimensional (temporal resolution, 15 seconds) MR imaging examinations. Readers rated enhancement shape, enhancement distribution, border architecture, enhancement intensity, presence of rim enhancement or internal septations, and the shape of the contrast material kinetic curve. Regression was performed for each feature individually and after adjustment for associated mammographic findings. Multivariate models were also constructed from multiple architectural and dynamic features. Areas under the receiver operating characteristic curve (Az values) were estimated for all models. RESULTS: There were 995 lesions in 854 women (mean age, 53 years +/- 12 [standard deviation]; range, 18-80 years) for whom pathology data were available. The absence of enhancement was associated with an 88% negative predictive value for cancer. Qualitative characterization of the dynamic enhancement pattern was associated with an Az value of 0.66 across all lesion architectures. Focal mass margins (Az = 0.76) and signal intensity (Az = 0.70) were highly predictive imaging features. Multivariate models were constructed with an Az value of 0.880. CONCLUSION: Architectural and dynamic features are important in breast MR imaging interpretation. Multivariate models involving feature assessment have a diagnostic accuracy superior to that of qualitative characterization of the dynamic enhancement pattern.

Adolescent↗
PubMed1999

A cost effective approach to the investigation of syncope: relative merit of different diagnostic strategies.

OBJECTIVE: To compare the cost effectiveness of a conventional diagnostic work-up with that of several different diagnostic cascades for the investigation of undifferentiated syncope. DESIGN: A MEDLINE search established a weighted estimate of diagnostic yield for several diagnostic investigations. 'High-end' and 'low-end' cost estimates were calculated for these investigations based on figures from four representative Canadian tertiary care centres in four different provinces. Several diagnostic models were applied to a hypothetical cohort of 100 patients with undifferentiated syncope. RESULTS: The conventional diagnostic cascade resulted in a diagnosis in 85% of patients, at a cost per diagnosis of $467 to $959. The optimal model increased the diagnostic yield to 98.9%, at a cost of $460 to $1043 per diagnosed patient. CONCLUSION: A combination of new technology and selective use of investigations has the potential to raise diagnostic yield without appreciably increasing cost per diagnosis.

Algorithms↗
PubMed1991

Diagnostic plots in Cox's regression model.

Two diagnostic plots are presented for validating the fitting of a Cox proportional hazards model. The added variable plot is developed to assess the effect of adding a covariate to the model. The constructed variable plot is applied to detect nonlinearity of a fitted covariate. Both plots are also useful for identifying influential observations on the issues of interest. The methods are illustrated on examples of multiple myeloma and lung cancer data.

Analysis of Variance↗
PubMed2002

Mechanistic modelling in large case-control studies of lung cancer risk from smoking.

The two-step clonal expansion (TSCE) model is applied to large case-control studies, frequency matched for age, which allow estimation of the RR of lung tumour risk caused by smoking. For estimating background hazard rates, mortality data from the study areas are used to supplement the case-control data. Two approaches are used to analyse the data, based on the unconditional and the conditional likelihoods. They are demonstrated to give nearly identical results. Some model diagnostics are performed and demonstrate a good model fit. Our results indicate that smoking acts on the promotion and transformation parameters, but not on the initiation parameter of the TSCE model. The fitted relative risk of current smokers peaks between ages 50 and 60 years. The relative risk of male ex-smokers decreases strongly with time since end of exposure, but does not reach the risk of non-smokers, and does not decrease as much as for female ex-smokers.

Adult↗
PubMed2005

Using stochastic differential equations for PK/PD model development.

A method for PK/PD model development based on stochastic differential equation models is proposed. The new method has a number of advantages compared to conventional methods. In particular, the new method avoids the exhaustive trial-and-error based search often conducted to determine the most appropriate model structure, because it allows information about the appropriate model structure to be extracted directly from data. This is accomplished through quantification of the uncertainty of the individual parts of an initial model, by means of which tools for performing model diagnostics can be constructed and guidelines for model improvement provided. Furthermore, the new method allows time-variations in key parameters to be tracked and visualized graphically, which allows important functional relationships to be revealed. Using simulated data, the performance of the new method is demonstrated by means of two examples. The first example shows how, starting from a simple assumption of linear PK, the method can be used to determine the correct nonlinear model for describing the PK of a drug following an oral dose. The second example shows how, starting from a simple assumption of no drug effect, the method can be used to determine the correct model for the nonlinear effect of a drug with known PK in an indirect response model.

Algorithms↗
PubMed2000

Prospective evaluation of three different models for the pre-operative diagnosis of ovarian cancer.

OBJECTIVE: To test the accuracy of the risk of malignancy index, the revised risk of malignancy index and Tailor's regression model to diagnose malignancy in women with known adnexal masses. DESIGN: Prospective collaborative study. SETTING: Gynaecology Assessment Unit, Department of Obstetrics and Gynaecology, King's College Hospital, London. SAMPLE: Sixty-one women with known adnexal masses were examined pre-operatively. Women were recruited from three South London hospitals. METHODS: The demographic, biochemical and sonographic data recorded for each patient included: age; menopausal status; CA125 levels; tumour volume; ultrasound characteristics; and Doppler blood flow analysis (peak and mean blood velocities, the pulsatility and resistance indices). The diagnosis of malignancy was made for each woman using all three models and the results compared with the final histopathological diagnosis. RESULTS: Thirty-eight women had benign tumours and 23 had ovarian cancer. Women with malignant tumours were significantly older than those with benign masses. There were also significant differences in CA125 levels, locularity, presence of papillary proliferations and ascites between the two groups. Tailor's regression model achieved a 43% sensitivity and 92% specificity in the diagnosis of malignancy. This compared with a 74% sensitivity and 92% specificity with the risk of malignancy model, and a 74% sensitivity and 89% specificity with the revised risk of malignancy model. CONCLUSION: When applied prospectively all three diagnostic models performed less accurately than originally reported, despite clinical signs of malignancy being present in many cases. It is likely that their accuracy would be even less in a population of women in whom there was a substantial clinical uncertainty. Intra-tumoral blood velocity and CA125 levels were the best individual parameters for discrimination between benign and malignant tumours.

Adult↗
PubMed1998

[The choice of the optimal plan for treating dystopia of individual teeth combined with arch defects of the maxilla].

Treatment of patients requires cooperation of an orthodontist and prosthesis-maker as early as during treatment planning. An adequate clinical situation of treatment can be chosen only after preliminary modeling and prediction of results using dismountable diagnostic models of the jaws and computer simulation of the graphic scheme of the teeth position and transposition, described in this paper. Two-staged orthodontic and orthopedic treatment is needed for patients with early removed teeth and delayed prostheses, congenital cleft alveolar process and palate, and lack of two lateral incisors. However, for 25% of patient lacking two lateral incisors, orthodontic treatment alone is sufficient.

Adolescent↗
PubMed2002

Long-term survival of equine surgical colic cases. Part 2: modelling postoperative survival.

Colic surgery is a frequently performed operation with high postoperative mortality. This study was undertaken to identify variables associated with decreased postoperative survival. We used data from 321 horse years of postoperative survival time to model the probability of survival following recovery from colic surgery. Continuous variables were modelled using a 6 variable, penalised Cox regression model. This demonstrated approximately linear relationships between survival and the following variables: increase in packed cell volume (PCV), intestinal resection length, time to surgery (interval between onset of colic and surgery) and duration of surgery. No significant decrease in survival was demonstrated with increasing age of the patient or with heart rate. The only categorical variable to be significantly associated with decreased survival was epiploic foramen entrapment. The final, fixed effects Cox proportional hazards model of postoperative survival included the variables epiploic foramen entrapment, PCV, resection length and duration of surgery, each variable adjusted for the nonlinear relationship with time to surgery. Residual variation in postoperative survival attributable to professional personnel (referring veterinary surgeon, anaesthetist and surgeon) was explored by fitting each as a random effects term in the model. Little of the residual variation could be attributed to any category of personnel. Model diagnostics indicated little influence by individual outliers on model parameters and little evidence of subjects poorly predicted by the final model. The study highlights factors influencing the long-term survival of horses recovering from colic surgery and proposes a model that can be used to inform prognosis.

Animals↗
PubMed2003

Multiple sclerosis and employment barriers: a systemic perspective on diagnosis and intervention.

Although they have a recent work history, 70 to 80% of adults with multiple sclerosis are unemployed following their diagnosis. This high rate of unemployment constitutes a great loss of potential to the American economy. To help individuals with multiple sclerosis (MS) return to work or retain employment, rehabilitation professionals must understand the barriers resulting in unemployment and implement interventions to reduce or remove those concerns. In this article, Hershenson's systemic model of rehabilitation counseling is presented as a diagnostic scheme for identifying barriers to employment. Counselor consultation on barrier removal via reasonable accommodation is presented as one example of a rehabilitation intervention consistent with the systemic diagnostic model.

Counseling↗
PubMed1979

[Use of computer-aided x-ray diagnosis in oncology (author's transl)].

The introduction of computer-aided diagnostic reveals new perspectives for diagnostic decisions. The results of the hitherto used mathematical diagnostic models are represented. The Bayes's theorem as the most used model exhibited very different, in parts unsatisfactory results. More convenient seems to be multivariate models, like discriminant analysis. Hitherto the computer-sided diagnostic was used in a relative small number of differential diagnostic problems. There are yet many replying questions. It is necessary to compare the efficiency of the different mathematical-statistical methods and to search for optimal solution ways for all differential diagnostic problems.

Abdominal Neoplasms↗
PubMed1998

Heritability estimates from human twin data by incorporating historical prior information.

Bayesian methods are commonly used in some analyses of human genetic data, such as segregation and linkage analyses, but they are not typically used for analyses of human twin data. In this paper we develop a scheme for a Bayesian analysis of human twin data. We develop prior elicitation schemes to incorporate historical information. We consider three prior schemes: fully informative, semi-informative and noninformative. We use Markov chain Monte Carlo sampling algorithms to facilitate Bayesian computation and provide detailed implementation schemes. We also develop model diagnostics for assessing the goodness of fit of twin models. Using a simulation study, we show that if the purpose of the study is to estimate the intraclass correlations or heritability in twin studies, then the semi-informative prior is as informative as the fully informative prior. Finally, a real data example is used to illustrate the proposed methodologies.

Bayes Theorem↗
PubMed2002

Threatened miscarriage in general practice: diagnostic value of history taking and physical examination.

BACKGROUND: Ultrasonography, the gold standard for establishing a diagnosis in first-trimester vaginal bleeding, is not always readily avaliable. Medical history and gynaecological examination are then used instead, to make a provisional diagnosis. AIM: To determine the diagnostic value of history taking and physical examination in first-trimester bleeding, to differentiate between patients requiring immediate further diagnostic examination from those in whom an expectant policy will initially suffice. DESIGN OF STUDY: Prospective population-based cohort study. SETTING: Seventy-four general practices in Amsterdam. METHOD: Two hundred and twenty-five patients with first trimester vaginal bleeding were referred for an early pregnancy assessment. The data from 204 patients were analysed. Two diagnostic models were constructed based on symptoms and the results of gynaecological examination to identify diagnostic subgroups relevant to clinical practice. RESULTS: Model 1, which separates viable pregnancies from other diagnoses, increased pre-test probability from 47% to a post-test probability of 70%. Model 2, which enabled the identification of complete miscarriages, resulted in a post-test probability of 41% of a complete miscarriage, given a pre-test sample probability of 25%. The tentative diagnosis of a general practitioner, based entirely on clinical judgement, turned out to be a poor predictor for the ultrasonographically confirmed diagnosis (pre-test probability of 47% changed to a post-test probability of 58%). CONCLUSION: This study shows that, in first trimester bleeding, neither statistical prediction models based on signs and symptoms, nor clinical judgement, are valid replacements for ultrasonographic assessment in establishing a diagnosis.

Abortion, Threatened↗
PubMed1993

Iron-deficiency anemia and thalassemia trait differentiated by simple hematological tests and serum iron concentrations.

The diagnostic value of common hematology tests in differentiating between thalassemia trait and iron-deficiency anemia (IDA) was assessed. Serum iron concentration was included in a second stage of the diagnostic model and its predictive contribution was determined. After applying discriminant analysis to the data, minimization of Wilks's lambda (lambda) criterion was used to select the best predictive variables. A training sample of 754 subjects previously classified as either IDA (428) or thalassemia trait (326) was used to determine the classification rule. When serum iron concentrations were included, the model showed a higher predictive capacity than that constructed from hematological variables only (D = 2.342 RBC - 0.079 Hb + 3.627 log[Fe] - 6.459, where D = discriminant score). The sensitivity, specificity, and diagnostic efficiency associated with this model, as assessed on a control sample of 256 patients (137 thalassemia and 119 IDA), were 94.2%, 91.6%, and 93.0%, respectively. This model, when compared with those of other authors, has the highest diagnostic efficiency.

Anemia, Hypochromic↗