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PubMed2001

Distinguishing the benign and malignant adnexal mass: an external validation of prognostic models.

OBJECTIVE: Because external validation of the present models has not been reported, the purpose of the present study was to assess existing diagnostic models that are used to distinguish malignant from benign masses. METHODS: We tested the performance of existing models in a prospectively assembled data set of 170 patients with an adnexal mass. Twenty-one models that have been reported previously were assessed. The models were based on combinations of ultrasound findings, color Doppler tests, CA-125 measurement, age, and/or menopausal status. For each model, we constructed ROC curves and calculated an area under the ROC curve. RESULTS: Of the 170 adnexal masses that were operated on, 30 (18%) were malignant. The area under the ROC curve of 21 models that were externally validated varied between 0.69 and 0.90. We found the performance of the existing models to be inferior to the performance reported in the initial studies. Even models that incorporated multiple diagnostic tools and that were developed using logistic regression models or neural networks had an area under the ROC curve of 0.86 at maximum. In the case where we focused on almost perfect sensitivity, the highest specificities varied between 0.45 and 0.60. CONCLUSION: Although diagnostic models might be of value in the preoperative assessment of the adnexal mass, their diagnostic performance is not as good as that reported in the original publications.

Adnexal Diseases↗
PubMed2005

SAPS 3--From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission.

OBJECTIVE: To develop a model to assess severity of illness and predict vital status at hospital discharge based on ICU admission data. DESIGN: Prospective multicentre, multinational cohort study. PATIENTS AND SETTING: A total of 16,784 patients consecutively admitted to 303 intensive care units from 14 October to 15 December 2002. MEASUREMENTS AND RESULTS: ICU admission data (recorded within +/-1 h) were used, describing: prior chronic conditions and diseases; circumstances related to and physiologic derangement at ICU admission. Selection of variables for inclusion into the model used different complementary strategies. For cross-validation, the model-building procedure was run five times, using randomly selected four fifths of the sample as a development- and the remaining fifth as validation-set. Logistic regression methods were then used to reduce complexity of the model. Final estimates of regression coefficients were determined by use of multilevel logistic regression. Variables selection and weighting were further checked by bootstraping (at patient level and at ICU level). Twenty variables were selected for the final model, which exhibited good discrimination (aROC curve 0.848), without major differences across patient typologies. Calibration was also satisfactory (Hosmer-Lemeshow goodness-of-fit test H=10.56, p=0.39, C=14.29, p=0.16). Customized equations for major areas of the world were computed and demonstrate a good overall goodness-of-fit. CONCLUSIONS: The SAPS 3 admission score is able to predict vital status at hospital discharge with use of data recorded at ICU admission. Furthermore, SAPS 3 conceptually dissociates evaluation of the individual patient from evaluation of the ICU and thus allows them to be assessed at their respective reference levels.

Adult↗
PubMed1981

A prognostic model for clinical stage I melanoma of the trunk. Location near the midline is not an independent risk factor for recurrent disease.

Fifteen variables were studied for their usefulness in predicting recurrent disease in 254 patients with clinical stage I melanoma of the trunk. Thickness of the primary tumor correctly predicted outcome with an accuracy of 90 percent or greater in 176 patients with melanoma primaries with a thickness of less than 1.70 mm or 5.5 mm or greater. No other variables significantly increased predictive accuracy over these ranges of thickness. A Cox proportional hazards analysis of the remaining 78 patients with primary tumors 1.70 to 5.49 mm thick demonstrated that the following four variables functioned as independent risk factors for recurrent disease: (1) thickness of the primary tumor (p = 0.0005), (2) mitoses/mm2 greater than 6 (p = 0.006), (3) a nearly absent or minimal lymphocyte response at the base of the tumor (p = 0.009), and (4) location on the upper trunk (p = 0.03). Trunk lesions located near the midline did not have a worse prognosis than more lateral melanomas of similar thickness.

Female↗
PubMed1995

Comparison of two prognostic models predicting survival in patients with malignant melanoma.

Accurate predictions of prognosis are important in the clinical management of patients with malignant melanoma. Primary lesions from 55 patients with cutaneous melanoma, having 10 or more years of clinical follow-up, were evaluated by two models predicting patient survival. One model was simple and relied solely on tumor thickness. The other model was complex and considered stage of tumor progression, and six clinical and histological variables. Accuracy of the two models was determined by retrospective review of the medical record, and the predictive power of each model was compared by receiver operating characteristic (ROC) curve analysis. The area under the ROC curve (a measure of the "goodness" of the model) for the single variable model was 0.70 +/- 0.0775 standard error (SE), and the area under the ROC curve for the multiple variable model was 0.77 +/- 0.0779 SE. Although a modest improvement in predictive power is suggested for the multiple variable model, the SEs for the two models overlap, and the difference is not statistically significant. Further study using a larger database may be required to determine definitively if the multiple variable model significantly increases the ability to predict patient survival or death, and make better clinical decisions.

Adult↗
PubMed1990

Use of prognostic models for assessment of value of liver transplantation in primary biliary cirrhosis.

To examine the effectiveness of liver transplantation (LTx) for the treatment of primary biliary cirrhosis (PBC) the actual survival of 30 PBC patients who received liver grafts was compared with predictions of what survival would have been without transplantation. Three models, based on Cox' regression analysis, were used. Two models were derived from survival of PBC patients in drug trials and the third from cirrhotic patients who did not receive transplants. Observed and expected survival were compared for a follow-up time of 7 years. After 1 year the difference in favour of LTx was small, but after 5 years survival with LTx exceeded all predicted survival probabilities without LTx. After 3 years every year of follow-up added about 0.3 years to expected survival gain per transplanted patient, resulting in 1.5 to 2.3 life-years gained at 7 years' follow-up, depending on the model used. The benefit was greatest for patients in Child-Pugh classes B and C. The consistency between the three models in their predictions supports the validity of the use of predictive models in the indirect assessment of LTx.

Actuarial Analysis↗
PubMed2005

MELD score is a better prognostic model than Child-Turcotte-Pugh score or Discriminant Function score in patients with alcoholic hepatitis.

BACKGROUND/AIMS: The aim of the present study was to compare MELD score, Child-Turcotte-Pugh (CTP) score, modified Maddrey's Discriminant Function (DF) score, and the related variables in predicting in-hospital mortality of patients with alcoholic hepatitis. METHODS: A retrospective chart review and statistical analyses were done on 202 patients consecutively admitted for alcoholic hepatitis from 1997 to 2002 at the Liver Unit at Rancho Los Amigos Medical Center. RESULTS: Twenty-nine patients died during the hospitalization. Admission MELD score (OR 1.1, P=0.005), first week MELD score (OR 1.2, P<0.0001), and first week increase in MELD score (OR 1.3, P<0.0001) were independently associated with in-hospital mortality. The area under the receiver operating curve (AUC) for the first week increase in MELD score was higher compared to CTP score (P=0.0004) and DF score (P=0.059). Moreover, the first week MELD score >/=20 had the best sensitivity (91%) and specificity (85%) compared with admission or first week change MELD score. CONCLUSIONS: The present study indicates that in patients with alcoholic hepatitis, admission, first week, and first week change in MELD score are significantly independent predictors for in-hospital mortality. MELD score is a more valuable model than CTP or DF score in patients admitted with alcoholic hepatitis.

Adult↗
PubMed2003

Prognostic models of abdominal wound dehiscence after laparotomy.

BACKGROUND: Portions of the prospective, multi-institutional National Veterans Affairs Surgical Quality Improvement Program were used to develop and validate a perioperative risk index to predict abdominal wound dehiscence after laparotomy. METHODS: Perioperative data from 17,044 laparotomies resulting in 587 (3.4%) wound dehiscences performed at 132 Veterans Affairs Medical Centers between October 1, 1996, and September 30, 1998, were used to develop the model. Data from 17,763 laparotomies performed between October 1, 1998, and September 30, 2000, resulting in 562 (3.2%) dehiscences were used to validate the model. Models were developed using multivariable stepwise logistic regression with preoperative, intraoperative, and postoperative variables entered sequentially as independent predictors of wound dehiscence. The model was used to create a scoring system, designated the abdominal wound dehiscence risk index. RESULTS: Factors contributing significantly to the model and their point values (in parentheses) for the risk index include CVA with no residual deficit (4), history of COPD (4), current pneumonia (4), emergency procedure (6), operative time greater than 2.5 h (2), PGY 4 level resident as surgeon (3), clean wound classification (-3), superficial (5), or deep (17) wound infection, failure to wean from the ventilator (6), one or more complications other than dehiscence (7), and return to OR during admission (-11). Scores of 11-14 are predictive of 5% risk of dehiscence while scores of >14 predict 10% risk. CONCLUSIONS: This abdominal wound dehiscence risk index identifies patients at risk for dehiscence and may be useful in guiding perioperative management.

Abdomen↗
PubMed1999

Prognostic models of thirty-day mortality and morbidity after major pulmonary resection.

BACKGROUND: A part of the prospective, multi-institutional National Veterans Affairs Surgical Quality Improvement Program was developed to predict 30-day mortality and morbidity for patients undergoing a major pulmonary resection. METHODS: Perioperative data were acquired from 194,319 noncardiac surgical operations at 123 Veterans Affairs Medical Centers between October 1, 1991, and August 31, 1995. Current Procedural Terminology code-based analysis was undertaken for major pulmonary resections (lobectomy and pneumonectomy). Preoperative, intraoperative, and outcome variables were collected. The 30-day mortality and morbidity models were developed by means of multivariable stepwise logistic regression with the preoperative and intraoperative variables used as independent predictors of outcome. RESULTS: A total of 3516 patients (mean age 64 9 years) underwent either lobectomy (n = 2949) or pneumonectomy (n = 567). Thirty-day mortality was 4.0% for lobectomy (119/2949) and 11.5% for pneumonectomy (65/567). The preoperative predictors of 30-day mortality were albumin, do not resuscitate status, transfusion of more than 4 units, age, disseminated cancer, impaired sensorium, prothrombin time more than 12 seconds, type of operation, and dyspnea. When the intraoperative variables were considered, intraoperative blood loss was added to the preoperative model. In the presence of these intraoperative variables in the model, do not resuscitate status and prothrombin time more than 12 seconds were only marginally significant. Thirty-day morbidity, defined as the presence of 1 or more of the 21 predefined complications, was 23.8% for lobectomy (703/2949) and 25.7% for pneumonectomy (146/567). In multivariable models, independent preoperative predictors (P <.05) of 30-day morbidity were age, weight loss greater than 10% in the 6 months before surgery, history of chronic obstructive pulmonary disease, transfusion of more than 4 units, albumin, hemiplegia, smoking, and dyspnea. When intraoperative variables were added to the preoperative model, the duration of operation time and intraoperative transfusions were included in the model and albumin became marginally significant. CONCLUSIONS: This analysis identifies independent patient risk factors that are associated with 30-day mortality and morbidity for patients undergoing a major pulmonary resection. This series provides an initial risk-adjustment model for major pulmonary resections. Future refinements will allow comparative assessment of surgical outcomes and quality of care at many institutions.

Adult↗