The triple-marker test in predicting fetal aneuploidy: a compromise between sensitivity and specificity.

OBJECTIVE: to review the contribution of unconjugated estriol in Down's syndrome detection, and influence of maternal age, cut-off choice, and population specificity on the balance between triple-marker test sensitivity and specificity. STUDY DESIGN: Prenatal karyotyping was performed in 2833 pregnant women, 73% of them over the age of 34. Duration of gestation was determined by ultrasound in 98% of women. Prior to amniocentesis, the serum levels of alpha-fetoprotein, human chorionic gonadotropin and unconjugated estriol were evaluated and corrected for weight. The risk of trisomy 21 was calculated for the first 986 subjects using default medians, and for 1847 by our population-specific medians. The cut-off was initially 1:300 at term, but the 1:100 and 1:200 risks were also tested. Down syndrome risk was calculated with alpha-fetoprotein and human chorionic gonadotropin combination as well. Linear logistic regression model was performed to test the ability of aneuploidy markers to classify patients into normal and trisomic groups. RESULTS: There were twelve cases of Down's syndrome, seven of trisomy 18, four of trisomy 13, and one trisomy 22. Four cases of aneuploidy (16.7%) referred to women younger than 35. With the cut-off risk of 1:300, detection rate was 87.5% and specificity 63.3%, and with 1:100, 66.7% and 79.5%, respectively. The sensitivity for Down's syndrome was from 75% for cut-off=1:100 to 92% for cut-off=1:300, while detection of other trisomies was less successful (58% and 83%, respectively). Exclusion of unconjugated estriol MoM from the risk calculations reduced detection rate by 33% and improved specificity by 4% independently of cut-off choice. Linear logistic regression analysis showed that only unconjugated estriol was able to correctly classify patients between normal and trisomy 21 (p=0.011, odds ratio=1.445), and normal and trisomy 18 (p=0.0023, odds ratio=1.96) groups. CONCLUSIONS: The unconjugated estriol significantly contributes in Down's syndrome detection with cost of slightly reduced specificity. The 1:300 risk caused an unfavorable compromise between sensitivity and specificity. A higher cut-off, 1:100, would indicate performance of amniocentesis in women aged 39 years and older, and in those aged 35-39 only after the screen-positive result.

Holistic approach to analysis of medical data: vulvar cancer.

This paper continues the series of studies introducing holistic approach to analysis of clinical data. Namely, besides the information regarding his/her disease, each hospitalized cancer patient also provides the variety of data regarding his/her psychological, cultural, social, economical, genetic, constitutional and medical background. The aim of this study was to introduce a holistic approach to analysis of medical data, in this case clinical data regarding cancer of the vulva. Such approach requires the collection of data regarding different aspects of the cancer patients, and after the satisfactory sample size is obtained (which should be at least five times greater than the number of examined patient characteristics), the performance of factor analysis. In this study, the authors have processed the data regarding 25 characteristics of all 755 vulvar cancer patients treated between 1938 and 1990 at the Department for Gynecological Oncology of the University Hospital for Gynecology and Obstetrics, Zagreb, Croatia. In factor analysis, the principal components were rotated after the initial extraction (the authors recommended the use of oblimin rotation) in order to obtain better ground for interpretation of the obtained results. The next step in this approach was the stepwise exclusion of characteristics with smallest commonality according to Kaiser-Meyer-Olkin criteria, and retaining the characteristics and components with the most significant impact on the explained system variance. When the number of principal components and initial analyzed characteristics was reduced to 3-4 and 7-10, respectively, the ultimate interpretations and conclusions were made. This approach outlined some clusters of correlations between medical data which are difficult to identify using other statistical procedures, primarily the impacts of various socioeconomic and hereditary-constitutional variables on overall survival.

Holistic approach to analysis of medical data: cancer of the corpus uteri.

Besides the information regarding his/her disease, each hospitalized cancer patient also provides the variety of data regarding his/her psychological, cultural, social, economical, genetic, constitutional and medical background. The aim of this study was to introduce a holistic approach to analysis of medical data, in this case clinical data regarding cancer of the corpus uteri. Such approach requires the collection of data regarding different aspects of the cancer patient, and after the satisfactory sample size is obtained (which should be at least five times greater than the number of examined patient characteristics), the performance of factor analysis. In this study, the authors have processed the data regarding 25 characteristics of 928 corpus uteri cancer patients treated between 1980 and 1990 at the Department for Gynecological Oncology of the University Hospital for Gynecology and Obstetrics, Zagreb, Croatia. In factor analysis, the principal components were rotated after the initial extraction (the authors recommended the use of oblimin rotation) in order to obtain better ground for interpretation of the obtained results. The next step in this approach was the stepwise exclusion of characteristics with smallest communalities according to Kaiser-Meyer-Olkin criteria, and retaining the characteristics and components with the most significant impact on the explained system variance. When the number of principal components and initial analyzed characteristics was reduced to 3-4 and 7-10, respectively, the ultimate interpretations and conclusions were made. This approach outlined some clusters of correlations between medical data which are difficult to identify using other statistical procedures, primarily the impacts of various socioeconomic and hereditary-constitutional variables on overall survival.

Transvaginal color flow imaging of the uterine artery during fertile period and postmenopause.

Transvaginal sonography with color flow mapping has been used in order to study various parts of uterine circulation during fertile period and postmenopause. The Doppler wave forms were analysed by pulsatility index and maximum systolic velocity of uterine artery and its ascending branches. A significantly lower vascular resistance was established in distal parts of the uterine artery. This finding could very likely represent a consequence of the effect of ovarian hormones on the vessel wall during the cycle. That might be a physiological basis for capability of fertilisation and carrying the normal pregnancy and child birth. Furthermore, it has been shown that during postmenopause, when ovaries normally cease steroid hormone production, it is difficult to detect wave forms in common uterine artery. However, postmenopausal extraovarian production of estrogen increases uterine flow and may precede hyperplastic or malignant changes of the endometrium. In women with proven pelvic masses, abnormal waveforms were recorded showing decreased uterine impedance and increased flow velocities.

Factor analysis of medical data of patients with primary and metastatic vaginal cancer.

This study adds up to the series of studies on application of factorial designs to analysis of cancer patients medical data. Namely, besides the information regarding his/her disease, each hospitalized cancer patient also provides the variety of data regarding his/her psychological, cultural, social, economical, genetic, constitutional and medical background. The aim of this particular study was to analyze clinical data in patients with primary and metastatic vaginal cancer and to compare them with the results of factor analytic approach in some other gynecological cancers, namely vulvar and cervical cancer. In this particular study the authors have processed the data regarding 25 characteristics of 200 consecutive patients with primary vaginal cancer and 300 consecutive patients with metastatic vaginal cancer treated between 1980 and 1994 at the Department for Gynecological Oncology of the University Hospital for Gynecology and Obstetrics, Zagreb, Croatia. The results revealed numerous repeating clusters of variable correlations across all four factor analyses in patients with cervical, vulvar, primary and metastatic vaginal cancers.