The performance of human papillomavirus high-risk DNA testing in the screening and diagnostic settings.

OBJECTIVE: We sought to evaluate the performance of the human papillomavirus high-risk DNA test in patients 30 years and older. MATERIALS AND METHODS: Screening (n=835) and diagnosis (n=518) groups were defined based on prior Papanicolaou smear results as part of a clinical trial for cervical cancer detection. We compared the Hybrid Capture II (HCII) test result with the worst histologic report. We used cervical intraepithelial neoplasia (CIN) 2/3 or worse as the reference of disease. We calculated sensitivities, specificities, positive and negative likelihood ratios (LR+ and LR-), receiver operating characteristic (ROC) curves, and areas under the ROC curves for the HCII test. We also considered alternative strategies, including Papanicolaou smear, a combination of Papanicolaou smear and the HCII test, a sequence of Papanicolaou smear followed by the HCII test, and a sequence of the HCII test followed by Papanicolaou smear. RESULTS: For the screening group, the sensitivity was 0.69 and the specificity was 0.93; the area under the ROC curve was 0.81. The LR+ and LR- were 10.24 and 0.34, respectively. For the diagnosis group, the sensitivity was 0.88 and the specificity was 0.78; the area under the ROC curve was 0.83. The LR+ and LR- were 4.06 and 0.14, respectively. Sequential testing showed little or no improvement over the combination testing. CONCLUSIONS: The HCII test in the screening group had a greater LR+ for the detection of CIN 2/3 or worse. HCII testing may be an additional screening tool for cervical cancer in women 30 years and older.

A nonparametric method of comparing the partial areas under two correlated receiver operating characteristic curves

A non-parametric method was developed and tested to compare the partial areas under two correlated Receiver Operating Characteristic curves. Based on the theory of generalized U-statistics the mathematical formulas have been derived for computing ROC area, and the variance and covariance between the portions of two ROC curves. A practical SAS application also has been developed to facilitate the calculations. The accuracy of the non-parametric method was evaluated by comparing it to other methods. By applying our method to the data from a published ROC analysis of CT image, our results are very close to theirs. A hypothetical example was used to demonstrate the effects of two crossed ROC curves. The two ROC areas are the same. However each portion of the area between two ROC curves were found to be significantly different by the partial ROC curve analysis. For computation of ROC curves with large scales, such as a logistic regression model, we applied our method to the breast cancer study with Medicare claims data. It yielded the same ROC area computation as the SAS Logistic procedure. Our method also provides an alternative to the global summary of ROC area comparison by directly comparing the true-positive rates for two regression models and by determining the range of false-positive values where the models differ. ^

Molecular markers of human papillomavirus (HPV) infection and epidemiologic risk factors for squamous intraepithelial lesions (SIL) of the cervix

Infection with certain types of HPV is a necessary event in the development of cervical carcinoma; however, not all women who become infected will progress. While much is known about the molecular influence of HPV E6 and E7 proteins on the malignant transformation, little is known about the additional factors needed to drive the process. Currently, conventional cervical screening is insufficient at identifying women who are likely to progress from premalignant lesions to carcinoma. Aneuploidy and chromatin texture from image cytometry have been suggested as quantitative measures of nuclear damage in premalignant lesions and cancer, and traditional epidemiologic studies have identified potential factors to aid in the discrimination of those lesions likely to progress. ^ In the current study, real-time PCR was used to quantitate mRNA expression of the E7 gene in women exhibiting normal epithelium, LSIL, and HSIL. Quantitative cytometry was used to gather information about the DNA index and chromatin features of cells from the same women. Logistic regression modeling was used to establish predictor variables for histologic grade based on the traditional epidemiologic risk factors and molecular markers. ^ Prevalence of mRNA transcripts was lower among women with normal histology (27%) than for women with LSIL (40%) and HSIL (37%) with mean levels ranging from 2.0 to 4.2. The transcriptional activity of HPV 18 was higher than that of HPV 16 and increased with increasing level of dysplasia, reinforcing the more aggressive nature of HPV 18. DNA index and mRNA level increased with increasing histological grade. Chromatin score was not correlated with histology but was higher for HPV 18 samples and those with both HPV 18 and HPV 16. However, chromatin score and DNA index were not correlated with mRNA levels. The most predictive variables in the regression modeling were mRNA level, DNA index, parity, and age, and the ROC curves for LSIL and HSIL indicated excellent discrimination. ^ Real-time PCR of viral transcripts could provide a more efficient method to analyze the oncogenic potential within cells from cervical swabs. Epidemiological modeling of malignant progression in the cervix should include molecular markers, as well as the traditional epidemiological risk factors. ^

Comparison of Bispectral Index (BIS) and Patient State Index (PSI) as objective measures of sedation and analgesia in critically ill/injured patients

Critically ill and injured patients require pain relief and sedation to reduce the body's stress response and to facilitate painful diagnostic and therapeutic procedures. Presently, the level of sedation and analgesia is guided by the use of clinical scores which can be unreliable. There is therefore, a need for an objective measure of sedation and analgesia. The Bispectral Index (BIS) and Patient State Index (PSI) were recently introduced into clinical practice as objective measures of the depth of analgesia and sedation. ^ Aim. To compare the different measures of sedation and analgesia (BIS and PSI) to the standard and commonly used modified Ramsay Score (MRS) and determine if the monitors can be used interchangeably. ^ Methods. MRS, BIS and PSI values were obtained in 50 postoperative cardiac surgery patients requiring analgesia and sedation from June to December 2004. The MRS, BIS and PSI values were assessed hourly for up to 6-h by a single observer. ^ The relationship between BIS and PSI values were explored using scatter plots and correlation between MRS, BIS and PSI was determined using Spearman's correlation coefficient. Intra-class correlation (ICC) was used to determine the inter-rater reliability of MRS, BIS and PSI. Kappa statistics was used to further evaluate the agreement between BIS and PSI at light, moderate and deep levels of sedation. ^ Results. There was a positive correlation between BIS and PSI values (Rho = 0.731, p<0.001). Intra-class correlation between BIS and PSI was 0.58, MRS and BIS 0.43 and MRS and PSI 0.27. Using Kappa statistics, agreement between MRS and BIS was 0.35 (95% CI: 0.27–0.43) and for MRS and PSI was 0.21 (95% CI: 0.15–0.28). The kappa statistic for BIS and PSI was 0.45 (95% CI: 0.37–0.52). Receiver operating characteristics (ROC) curves constructed to detect undersedation indicated an area under the curve (AUC) of 0.91 (95% CI = 0.87 to 0.94) for the BIS and 0.84 (95% CI = 0.79 to 0.88) for the PSI. For detection of oversedation, AUC for the BIS was 0.89 (95% CI = 0.84 to 0.92) and 0.80 (95% CI = 0.75 to 0.85) for the PSI. ^ Conclusions. There is a statistically significant positive correlation between the BIS and PSI but poor correlation and poor test agreement between the MRS and BIS as well as MRS and PSI. Both the BIS and PSI demonstrated a high level of prediction for undersedation and oversedation; however, the BIS and PSI can not be considered interchangeable monitors of sedation. ^

Effect of smoking on the association between periodontitis and incidence of coronary heart disease: The Atherosclerosis Risk in Communities Study

Multiple studies have shown an association between periodontitis and coronary heart disease due to the chronic inflammatory nature of periodontitis. Also, studies have indicated similar risk factors and patho-physiologic mechanisms for periodontitis and CHD. Among these factors, smoking has been the most discussed common risk factor and some studies suggested the periodontitis - CHD association to be largely a result of confounding due to smoking or inadequate adjustment for it. We conducted a secondary data analysis of the Dental ARIC Study, an ancillary study to the ARIC Study, to evaluate the effect of smoking on the periodontitis - CHD association using three periodontitis classifications namely, BGI, AAP-CDC, and Dental-ARIC classification (Beck et al 2001). We also compared these results with edentulous ARIC participants. Using Cox proportional hazard models, we found that the individuals with the most severe form of periodontitis in each of the three classifications (BGI: HR = 1.56, 95%CI: 1.15 – 2.13; AAP-CDC: HR = 1.42, 95%CI: 1.13 – 1.79; and Dental-ARIC: HR = 1.49, 95%CI: 1.22 – 1.83) were at a significantly higher risk of incident CHD in the unadjusted models; whereas only BGI-P3 showed statistically significant increased risk in the smoking adjusted models (HR = 1.43, 95%CI: 1.04 – 1.96). However none of the categories in any of the classifications showed significant association when a list of traditional CHD risk factors was introduced into the models. On the other hand, edentulous participants showed significant results when compared to the dentate ARIC participants in the crude (HR = 1.56, 95%CI: 1.34 – 1.82); smoking adjusted (HR = 1.39, 95%CI: 1.18 – 1.64) age, race and sex adjusted (HR = 1.52, 95%CI: 1.30 – 1.77); and ARIC traditional risk factors (except smoking) adjusted (HR = 1.27, 95%CI: 1.02 – 1.57) models. Also, the risk remained significantly higher even when smoking was introduced in the age, sex and race adjusted model (HR = 1.38, 95%CI: 1.17 – 1.63). Smoking did not reduce the hazard ratio by more than 8% when it was included in any of the Cox models. ^ This is the first study to include the three most recent case definitions of periodontitis simultaneously while looking at its association with incident coronary heart disease. We found smoking to be partially confounding the periodontitis and coronary heart disease association and edentulism to be significantly associated with incident CHD even after adjusting for smoking and the ARIC traditional risk factors. The difference in the three periodontitis classifications was not found to be statistical significant when they were tested for equality of the area under their ROC curves but this should not be confused with their clinical significance.^

Prediction of sepsis in the burn intensive care unit patient

Sepsis is a significant cause for multiple organ failure and death in the burn patient, yet identification in this population is confounded by chronic hypermetabolism and impaired immune function. The purpose of this study was twofold: 1) determine the ability of the systemic inflammatory response syndrome (SIRS) and American Burn Association (ABA) criteria to predict sepsis in the burn patient; and 2) develop a model representing the best combination of clinical predictors associated with sepsis in the same population. A retrospective, case-controlled, within-patient comparison of burn patients admitted to a single intensive care unit (ICU) was conducted for the period January 2005 to September 2010. Blood culture results were paired with clinical condition: "positive-sick"; "negative-sick", and "screening-not sick". Data were collected for the 72 hours prior to each blood culture. The most significant predictors were evaluated using logistic regression, Generalized Estimating Equations (GEE) and ROC area under the curve (AUC) analyses to assess model predictive ability. Bootstrapping methods were employed to evaluate potential model over-fitting. Fifty-nine subjects were included, representing 177 culture periods. SIRS criteria were not found to be associated with culture type, with an average of 98% of subjects meeting criteria in the 3 days prior. ABA sepsis criteria were significantly different among culture type only on the day prior (p = 0.004). The variables identified for the model included: heart rate>130 beats/min, mean blood pressure<60 mmHg, base deficit<-6 mEq/L, temperature>36°C, use of vasoactive medications, and glucose>150 mg/d1. The model was significant in predicting "positive culture-sick" and sepsis state, with AUC of 0.775 (p < 0.001) and 0.714 (p < .001), respectively; comparatively, the ABA criteria AUC was 0.619 (p = 0.028) and 0.597 (p = .035), respectively. SIRS criteria are not appropriate for identifying sepsis in the burn population. The ABA criteria perform better, but only for the day prior to positive blood culture results. The time period useful to diagnose sepsis using clinical criteria may be limited to 24 hours. A combination of predictors is superior to individual variable trends, yet algorithms or computer support will be necessary for the clinician to find such models useful. ^

Performance of HbA1c for classifying diabetes and diagnostic threshold for diabetes among the Mexican American border community

Objective. In 2009, the International Expert Committee recommended the use of HbA1c test for diagnosis of diabetes. Although it has been recommended for the diagnosis of diabetes, its precise test performance among Mexican Americans is uncertain. A strong “gold standard” would rely on repeated blood glucose measurement on different days, which is the recommended method for diagnosing diabetes in clinical practice. Our objective was to assess test performance of HbA1c in detecting diabetes and pre-diabetes against repeated fasting blood glucose measurement for the Mexican American population living in United States-Mexico border. Moreover, we wanted to find out a specific and precise threshold value of HbA1c for Diabetes Mellitus (DM) and pre-diabetes for this high-risk population which might assist in better diagnosis and better management of patient diabetes. ^ Research design and methods. We used CCHC dataset for our study. In 2004, the Cameron County Hispanic Cohort (CCHC), now numbering 2,574, was established drawn from randomly selected households on the basis of 2000 Census tract data. The CCHC study randomly selected a subset of people (aged 18-64 years) in CCHC cohort households to determine the influence of SES on diabetes and obesity. Among the participants in Cohort-2000, 67.15% are female; all are Hispanic. ^ Individuals were defined as having diabetes mellitus (Fasting plasma glucose [FPG] ≥ 126 mg/dL or pre-diabetes (100 ≤ FPG < 126 mg/dL). HbA1c test performance was evaluated using receiver operator characteristic (ROC) curves. Moreover, change-point models were used to determine HbA1c thresholds compatible with FPG thresholds for diabetes and pre-diabetes. ^ Results. When assessing Fasting Plasma Glucose (FPG) is used to detect diabetes, the sensitivity and specificity of HbA1c≥ 6.5% was 75% and 87% respectively (area under the curve 0.895). Additionally, when assessing FPG to detect pre-diabetes, the sensitivity and specificity of HbA1c≥ 6.0% (ADA recommended threshold) was 18% and 90% respectively. The sensitivity and specificity of HbA1c≥ 5.7% (International Expert Committee recommended threshold) for detecting pre-diabetes was 31% and 78% respectively. ROC analyses suggest HbA1c as a sound predictor of diabetes mellitus (area under the curve 0.895) but a poorer predictor for pre-diabetes (area under the curve 0.632). ^ Conclusions. Our data support the current recommendations for use of HbA1c in the diagnosis of diabetes for the Mexican American population as it has shown reasonable sensitivity, specificity and accuracy against repeated FPG measures. However, use of HbA1c may be premature for detecting pre-diabetes in this specific population because of the poor sensitivity with FPG. It might be the case that HbA1c is differentiating the cases more effectively who are at risk of developing diabetes. Following these pre-diabetic individuals for a longer-term for the detection of incident diabetes may lead to more confirmatory result.^

External validation study of a clinical prediction rule for ambulation outcomes after traumatic spinal cord injury

The main objective of this study was to determine the external validity of a clinical prediction rule developed by the European Multicenter Study on Human Spinal Cord Injury (EM-SCI) to predict the ambulation outcomes 12 months after traumatic spinal cord injury. Data from the North American Clinical Trials Network (NACTN) data registry with approximately 500 SCI cases were used for this validity study. The predictive accuracy of the EM-SCI prognostic model was evaluated using calibration and discrimination based on 231 NACTN cases. The area under the receiver-operating-characteristics curve (ROC) curve was 0.927 (95% CI 0.894 – 0.959) for the EM-SCI model when applied to NACTN population. This is lower than the AUC of 0.956 (95% CI 0.936 – 0.976) reported for the EM-SCI population, but suggests that the EM-SCI clinical prediction rule distinguished well between those patients in the NACTN population who were able to achieve independent ambulation and those who did not achieve independent ambulation. The calibration curve suggests that higher the prediction score is, the better the probability of walking with the best prediction for AIS D patients. In conclusion, the EM-SCI clinical prediction rule was determined to be generalizable to the adult NACTN SCI population.^

The risk prediction for SPM and its impact on the survival in patients with head and neck squamous cell carcinoma

Head and Neck Squamous Cell Carcinoma (HNSCC) is the sixth common malignancy in the world, with high rates of developing second primary malignancy (SPM) and moderately low survival rates. This disease has become an enormous challenge in the cancer research and treatments. For HNSCC patients, a highly significant cause of post-treatment mortality and morbidity is the development of SPM. Hence, assessment of predicting the risk for the development of SPM would be very helpful for patients, clinicians and policy makers to estimate the survival of patients with HNSCC. In this study, we built a prognostic model to predict the risk of developing SPM in patients with newly diagnosed HNSCC. The dataset used in this research was obtained from The University of Texas MD Anderson Cancer Center. For the first aim, we used stepwise logistic regression to identify the prognostic factors for the development of SPM. Our final model contained cancer site and overall cancer stage as our risk factors for SPM. The Hosmer-Lemeshow test (p-value= 0.15>0.05) showed the final prognostic model fit the data well. The area under the ROC curve was 0.72 that suggested the discrimination ability of our model was acceptable. The internal validation confirmed the prognostic model was a good fit and the final prognostic model would not over optimistically predict the risk of SPM. This model needs external validation by using large data sample size before it can be generalized to predict SPM risk for other HNSCC patients. For the second aim, we utilized a multistate survival analysis approach to estimate the probability of death for HNSCC patients taking into consideration of the possibility of SPM. Patients without SPM were associated with longer survival. These findings suggest that the development of SPM could be a predictor of survival rates among the patients with HNSCC.^

AN EVALUATION OF THE CONSISTENCY OF IMRT PATIENT-SPECIFIC QA TECHNIQUES

To ensure the integrity of an intensity modulated radiation therapy (IMRT) treatment, each plan must be validated through a measurement-based quality assurance (QA) procedure, known as patient specific IMRT QA. Many methods of measurement and analysis have evolved for this QA. There is not a standard among clinical institutions, and many devices and action levels are used. Since the acceptance criteria determines if the dosimetric tools’ output passes the patient plan, it is important to see how these parameters influence the performance of the QA device. While analyzing the results of IMRT QA, it is important to understand the variability in the measurements. Due to the different form factors of the many QA methods, this reproducibility can be device dependent. These questions of patient-specific IMRT QA reproducibility and performance were investigated across five dosimeter systems: a helical diode array, radiographic film, ion chamber, diode array (AP field-by-field, AP composite, and rotational composite), and an in-house designed multiple ion chamber phantom. The reproducibility was gauged for each device by comparing the coefficients of variation (CV) across six patient plans. The performance of each device was determined by comparing each one’s ability to accurately label a plan as acceptable or unacceptable compared to a gold standard. All methods demonstrated a CV of less than 4%. Film proved to have the highest variability in QA measurement, likely due to the high level of user involvement in the readout and analysis. This is further shown by how the setup contributed more variation than the readout and analysis for all of the methods, except film. When evaluated for ability to correctly label acceptable and unacceptable plans, two distinct performance groups emerged with the helical diode array, AP composite diode array, film, and ion chamber in the better group; and the rotational composite and AP field-by-field diode array in the poorer group. Additionally, optimal threshold cutoffs were determined for each of the dosimetry systems. These findings, combined with practical considerations for factors such as labor and cost, can aid a clinic in its choice of an effective and safe patient-specific IMRT QA implementation.