A Note on the Asymptotic Variance of Survival Function in the Semi-Markov Model

In Malani and Neilsen (1992) we have proposed alternative estimates of survival function (for time to disease) using a simple marker that describes time to some intermediate stage in a disease process. In this paper we derive the asymptotic variance of one such proposed estimator using two different methods and compare terms of order 1/n when there is no censoring. In the absence of censoring the asymptotic variance obtained using the Greenwood type approach converges to exact variance up to terms involving 1/n. But the asymptotic variance obtained using the theory of the counting process and results from Voelkel and Crowley (1984) on semi-Markov processes has a different term of order 1/n. It is not clear to us at this point why the variance formulae using the latter approach give different results.

Semiparametric Methods for Semi-competing Risks Problem with Censoring and Truncation

Studies of chronic life-threatening diseases often involve both mortality and morbidity. In observational studies, the data may also be subject to administrative left truncation and right censoring. Since mortality and morbidity may be correlated and mortality may censor morbidity, the Lynden-Bell estimator for left truncated and right censored data may be biased for estimating the marginal survival function of the non-terminal event. We propose a semiparametric estimator for this survival function based on a joint model for the two time-to-event variables, which utilizes the gamma frailty specification in the region of the observable data. Firstly, we develop a novel estimator for the gamma frailty parameter under left truncation. Using this estimator, we then derive a closed form estimator for the marginal distribution of the non-terminal event. The large sample properties of the estimators are established via asymptotic theory. The methodology performs well with moderate sample sizes, both in simulations and in an analysis of data from a diabetes registry.

A semi-structured interview to assess visual hallucinations in older people

OBJECTIVE: Visual hallucinations are under-reported by patients and are often undiscovered by health professionals. There is no gold standard available to assess hallucinations. Our objective was to develop a reliable, valid, semi-structured interview for identifying and assessing visual hallucinations in older people with eye disease and cognitive impairment. METHODS: We piloted the North-East Visual Hallucinations Interview (NEVHI) in 80 older people with visual and/or cognitive impairment (patient group) and 34 older people without known risks of hallucinations (control group). The informants of 11 patients were interviewed separately. We established face validity, content validity, criterion validity, inter-rater agreement and the internal consistency of the NEVHI, and assessed the factor structure for questions evaluating emotions, cognitions, and behaviours associated with hallucinations. RESULTS: Recurrent visual hallucinations were common in the patient group (68.8%) and absent in controls (0%). The criterion, face and content validities were good and the internal consistency of screening questions for hallucinations was high (Cronbach alpha: 0.71). The inter-rater agreements for simple and complex hallucinations were good (Kappa 0.72 and 0.83, respectively). Four factors associated with experiencing hallucinations (perceived control, pleasantness, distress and awareness) were identified and explained a total variance of 73%. Informants gave more 'don't know answers' than patients throughout the interview (p = 0.008), especially to questions evaluating cognitions and emotions associated with hallucinations (p = 0.02). CONCLUSIONS: NEVHI is a comprehensive assessment tool, helpful to identify the presence of visual hallucinations and to quantify cognitions, emotions and behaviours associated with hallucinations.

Semi-automatic segmentation of fetal cardiac cavities: progress towards an automated fetal echocardiogram

OBJECTIVE: To develop a novel application of a tool for semi-automatic volume segmentation and adapt it for analysis of fetal cardiac cavities and vessels from heart volume datasets. METHODS: We studied retrospectively virtual cardiac volume cycles obtained with spatiotemporal image correlation (STIC) from six fetuses with postnatally confirmed diagnoses: four with normal hearts between 19 and 29 completed gestational weeks, one with d-transposition of the great arteries and one with hypoplastic left heart syndrome. The volumes were analyzed offline using a commercially available segmentation algorithm designed for ovarian folliculometry. Using this software, individual 'cavities' in a static volume are selected and assigned individual colors in cross-sections and in 3D-rendered views, and their dimensions (diameters and volumes) can be calculated. RESULTS: Individual segments of fetal cardiac cavities could be separated, adjacent segments merged and the resulting electronic casts studied in their spatial context. Volume measurements could also be performed. Exemplary images and interactive videoclips showing the segmented digital casts were generated. CONCLUSION: The approach presented here is an important step towards an automated fetal volume echocardiogram. It has the potential both to help in obtaining a correct structural diagnosis, and to generate exemplary visual displays of cardiac anatomy in normal and structurally abnormal cases for consultation and teaching.