Application of the principal stratification approach to the Faenza randomized experiment on breast self-examination.

In this article we present an extended framework based on the principal stratification approach (Frangakis and Rubin, 2002, Biometrics 58, 21-29), for the analysis of data from randomized experiments which suffer from treatment noncompliance, missing outcomes following treatment noncompliance, and "truncation by death." We are not aware of any previous work that addresses all these complications jointly. This framework is illustrated in the context of a randomized trial of breast self-examination.

Cross-sectional and longitudinal evaluation of uterine artery Doppler velocimetry for the prediction of pre-eclampsia in normotensive women with specific risk factors.

OBJECTIVE: To evaluate the performance, in the prediction of pre-eclampsia, of (1) an abnormal mean uterine artery resistance index (RI; cross-sectional index) at 24 weeks of gestation, (2) the individual longitudinal flow pattern of results observed at 16, 20 and 24 weeks of gestation and (3) a multiple logistic regression model including the individual longitudinal flow pattern and the mean RI at 24 weeks. METHODS: A total of 144 normotensive pregnant women with risk factors for pre-eclampsia were evaluated with uterine artery color Doppler at 16, 20 and 24 weeks' gestation. The following indices were obtained: (1) cross-sectional index: the mean RI of both uterine arteries at 24 weeks' gestation was calculated for each patient and considered abnormal when >/= 0.58; (2) longitudinal indices: the individual longitudinal flow pattern of mean RI of both the main uterine arteries at 16, 20 and 24 weeks' gestation was derived for each subject and defined as (a) the typical physiological flow pattern, with a trend of decrease in values or (b) the non-physiological flow pattern. The probability of having a pregnancy complicated by pre-eclampsia was also calculated by means of a multivariate logit model. The log-odds was modeled as a function of variables related to maternal characteristics, the individual longitudinal flow pattern indicator, and of the mean RI at 24 weeks' gestation as a continuous variable. RESULTS: Pregnancies had a physiological course in 108 (75%) women, while 36 (25%) women developed pre-eclampsia during the third trimester. For the prediction of pre-eclampsia, the use of an abnormal uterine artery RI index (> or = 0.58) at 24 weeks showed a sensitivity of 77.8%, a specificity of 67.6%, a positive predictive value (PPV) of 44.4% and a negative predictive value (NPV) of 90.1%, with a likelihood ratio (LR) for an abnormal test of 2.4; with the longitudinal flow pattern indicator, sensitivity was 88.9%, specificity 82.4%, PPV 62.7% and NPV 95.7%, with a LR for an abnormal test of 4.9; the use of a logit model yielded a sensitivity of 72.2%, a specificity of 90.7%, a PPV of 72.2% and a NPV of 90.7%, with a LR for an abnormal test of 8.0. CONCLUSIONS: In this study the use of an individual longitudinal flow pattern indicator resulted in improving accuracy in the prediction of pre-eclampsia as compared with the traditional cross-sectional mean RI at 24 weeks. A further increase in specificity and PPV was obtained using a logit model that includes the longitudinal flow pattern indicator and the cross-sectional RI at 24 weeks. Since both the longitudinal flow pattern indicator and the logit model showed a high performance in predicting pre-eclampsia in women with risk factors for impaired placentation, they might be used to identify a high-risk population in which preventive measures and/or therapeutic options might be tested.

Individual longitudinal patterns in biochemical and hematological markers for the early prediction of pre-eclampsia.

OBJECTIVE: To analyze the individual longitudinal patterns of maternal biochemical and hematological tests performed throughout gestation in order to predict at the 20th week of pregnancy the later development of pre-eclampsia. STUDY DESIGN: A longitudinal study was conducted on 187 white normotensive pregnant women all with a history of pre-eclampsia. Blood samples were performed at the 8th week of gestation and then every 4 weeks until the 36th week. The longitudinal patterns of urea, creatinine, uric acid, total proteins, hematocrit, red blood cells, hemoglobin, mean red cell volume, ferritin and iron were derived. By means of regression analysis, for each woman and each significant marker, a 'theoretical physiological pattern', from the 8th to the 20th week, was constructed. By comparing the observed values of each marker for each woman with her 'theoretical physiological pattern', variables indicating the match or mismatch to it were derived. Such variables were used, together with other maternal characteristics, in a logit regression for the probability of developing pre-eclampsia later in pregnancy. RESULTS: In 140 cases, pregnancies followed a physiological course, while 47 women developed pre-eclampsia during the third trimester. In the physiological gestations, the weekly mean values of creatinine, hematocrit, total proteins, uric acid and urea showed patterns that were significantly different from those of the pathological group. The logit model was able to classify correctly 96% of the physiological and 87% of the pathological pregnancies, with a negative predictive value of 96% and a positive predictive value of 89% (area under the receiver operator characteristics (ROC) curve 0.98). The ability of the model to predict later complications at the 20th week was confirmed by a validation procedure. CONCLUSION: The simultaneous use of individual longitudinal patterns of parameters, achieved non-invasively as part of the standard methods of antenatal care that provide a global evaluation of plasma volume expansion, showed a high ability to predict, early in pregnancy, the later development of pre-eclampsia.

Specification tests for random-effects transition models: an application to a model of the British youth training scheme.

We develop diagnostic tests for random-effects multi-spell multi-state models focusing on: independence between the unobserved heterogeneity and observed covariates; mutual independence of heterogeneity terms; and distributional form. They are applied to a transition model of the British youth labor market, revealing significant mis-specifications in our initial model, and allowing us to develop a considerably better-fitting specification that would have been difficult to reach by other means. The improved specification implies reduced estimates of the effectiveness of the youth training scheme (YTS), but we nevertheless retain the conclusion of significant positive effects of YTS on employment prospects.