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PubMed2005

[An information model as a method of mathematical processing of clinical material (chronic bronchitis as illustration)].

AIM: To design information clinical-prognostic formalized model of chronic bronchitis (CB). MATERIAL AND METHODS: The study of clinicofunctional, immunometabolic manifestations in CB remissions in 1135 CB patients and genealogical study of 24 families in three generations (83 persons) were performed. Clinical, functional, biochemical, immunological examinations were made. RESULTS: An algorithm of information model of CB consisting of 5 principal steps and technology of information processing of clinical material are proposed. A data matrix was developed in the form of blocks (passport data, former life style, complaints, disease history, characteristics of objective status, functional, clinical, biochemical, immunological parameters) and information analysis was made using a selected mathematical method (correlation, cluster, factorial, regression analyses). CONCLUSION: The proposed methodological approach allows assessment of interaction of such factors as heredity, environment, life style and their effect on CB risk, clinical picture, course; design of program of primary and secondary prophylaxis and assessment of treatment efficacy.

Algorithms↗

PubMed2025

Anoikis classification of lung squamous cell carcinoma reveals correlation with clinical prognosis and immune characteristics.

BACKGROUND: Anoikis is a new mode of cell death that has been shown to correlate significantly with tumors. However, the clinical prognostic significance of anoikis in lung squamous cell carcinoma (LUSC) remains poorly studied. METHODS: The differentially expressed ARGs and candidate genes were selected by the differential analysis to construct a predictive model. Independent prognostic gene was determined by Cox and LASSO analysis and we used the HCC95 and NCI H520 cell line to verify the gene function. We used the data from TCGA, GEO, GeneCards, and Harmonizome databases to analyze the immune microenvironment, functional enrichment, and drug sensitivity analysis. RESULTS: We identified 717 differentially expressed and selected 3 ARGs (FADD, SNAI1, and BAG4) to construct a predictive model. We found that SNAI1 is an independent prognostic gene and confirmed that knocking out the SNAI1 inhibited the HCC95/NCI H520 cell proliferation. We used single-sample gene-set enrichment analysis (ssGSEA) to evaluate the immune infiltration based on the 3 ARG expression levels. We constructed a risk score and provided a visual representation of the prophetic implications of the ARGs-based signature through a nomogram. We found 15 susceptible drugs in the high-risk group and 15 sensitive drugs in the low-risk group by the drug sensitivity analysis. CONCLUSION: We used ARGs to construct a prognosis model for LUSC that can accurately predict the prognosis of LUSC patients. ARGs, especially SNAI1, play an essential role in developing LUSC. These findings could provide individualized treatment plans and new research ideas for LUSC patients.

Humans↗

PubMedDate not supplied

A survival predictive model in patients undergoing radical resection of ampullary adenocarcinoma.

BACKGROUND/AIMS: Radical resection with either pancreaticoduodenectomy or pylorus-preserving pancreaticoduodenectomy is considered to be the standard treatment for most ampullary carcinomas, but the prognostic predictive model has not yet been developed. METHODOLOGY: The pretreatment, treatment, and follow-up variables of data of 47 patients undergoing radical resection for the ampullary carcinoma were analyzed to determine the favorable prognostic variables. Employing the Kaplan-Meier method, the cumulative survival rates of the ampullary carcinoma were calculated. By Cox regression model, a stepwise multivariate analysis was performed to analyze the contributing factors of the survival rate, and a predictive survival equation was obtained. RESULTS: With the results of the univariate analysis, the variables significantly associated with favorable prognosis were younger age (<63 years), TNM stage (stage I or II or III), and the degree of tumor differentiation (well or moderately differentiated). When the above three variables were examined as covariates by Cox regression in multivariate analysis, the TNM stage and the degree of tumor differentiation were independently correlated with the survival. A predictive survival equation obtained with the beta-coefficients of the above three variables was as follows: S (t) = [So (t)] P, P = exp (0.0234 x age - 1.8744 x tumor differentiation + 1.1576 x TNM stage) CONCLUSIONS: This predictive survival equation can predict the survival and the favorable outcome of patients treated with radical resection of ampullary carcinoma.

Actuarial Analysis↗

PubMed1999

An evaluation of intelligent prognostic systems for colorectal cancer.

In this paper we describe attempts at building a robust model for predicting the length of survival of patients with colorectal cancer. The aim of the research, reported in this paper, is to study the effective utilisation of artificial intelligence techniques in the medical domain. We suggest that an important research objective of proponents of intelligent prognostic systems must be to evaluate the additionality that AI techniques can bring to an already well-established field of medical prognosis. Towards this end, we compare a number of different AI techniques that lend themselves to the task of predicting survival in colorectal cancer patients. We describe the pros and cons of each of these methods using the usual metrics of accuracy and perspicuity. We then present the notion of intelligent hybrid systems and evaluate the role that they may potentially play in developing robust prognostic models. In particular we evaluate a hybrid system that utilises the k Nearest Neighbour technique in conjunction with Genetic Algorithms. We describe a number of innovations used within this hybrid paradigm used to build the prognostic model. We discuss the issue of censored patients and how this issue can be tackled within the various models used. In keeping with our objective of studying the additionality that AI techniques bring to building prognostic models, we use Cox's regression as a standard and compare each AI technique with it, attempting to discover their capabilities in enhancing prognostic methods in medicine. In doing so we address two main questions--which model fits the data best?, and are the results obtained by the various AI techniques significantly different from those of Cox's regression? We conclude this paper by discussing future enhancements to the work presented and lessons learned from the study to date.

Age Factors↗

PubMed1995

Plasma calprotectin: a new prognostic marker of survival in alcohol-induced cirrhosis.

Plasma levels of calprotectin were determined in 84 patients with alcohol-induced cirrhosis. Calprotectin is released from disintegrating neutrophils, and plasma levels seem to reflect activation and turnover of such cells. The purpose of the study was to investigate the degree of activation of neutrophils, which has been indicated to be increased and a cause of neutrophil exhaustion in these patients. Additionally, on follow-up after a median observation period of 559 days, we investigated the prognostic value of calprotectin for survival. No difference was found in calprotectin levels when comparing healthy controls with patients with compensated cirrhosis and those with decompensated cirrhosis. However, high calprotectin concentrations (> median) were a significant prognostic marker of poor survival (P = .001, log-rank test). Using a multivariate Cox proportional hazard model, the prognostic value of calprotectin seemed independent of severity of liver disease evaluated on eight clinical and biochemical variables of liver disease. Divided into groups by the median calprotectin concentration, analysis of survival was performed in the whole series of patients (n = 84) as well as in patients who were completely without signs of recent or actual infection (n = 54). In both groups, calprotectin levels (> median) showed a much higher prognostic value than albumin, prothrombin complex, bilirubin, and ascites. During follow-up, calprotectin levels (> median) were also a predictor of recurrent infection (P = .009). Thus, in patients with alcoholic cirrhosis, plasma calprotectin seems to be a new prognostic marker of survival, which seems independent of the severity of liver disease.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗

PubMed1997

Prognostic implications of qualitative assessment of left ventricular function compared to simple routine quantitative echocardiography.

OBJECTIVE: To compare the prognostic value of qualitative estimates of left ventricular function with that of routine simple quantitative indices used in echocardiography. DESIGN: Retrospective follow up study. SETTING: University hospital. PATIENTS: The records of 2,964 patients who had undergone echocardiography and who could be traced on the family health services register were examined; 919 cases were included in the study, and a further 458 were used to validate the statistical models for prognostic assessment. There were 928 exclusions on the basis of referral for or diagnosis of alternative conditions, and 659 because of incomplete collection of the qualitative and quantitative data used in the study. MAIN OUTCOME MEASURE: Survival over the study period. RESULTS: A qualitative "eyeball" estimate of left ventricular function was of prognostic significance (relative risk of poor v good, 2.248; P << 0.001; 95% confidence interval 1.620 to 3.119). None of the quantitative echocardiographic indices was of independent prognostic significance when all variables were tested simultaneously in the regression model. CONCLUSIONS: A qualitative echocardiographic estimate of left ventricular dysfunction is of prognostic value, supporting the view of many cardiologists who use their overall impression of left ventricular function at echocardiography as the basis for treatment decisions.

Adolescent↗

PubMed1985

[Mathematical modeling of the dynamics of the intensity of the mutation process. I. Formulation of the task and the general model].

Methodology is devised to construct dynamic models of the mutation process intensity under quasi-stationary environmental conditions and limited experimental information. Laws of distribution of unknown parameters of dynamic models and prognostic values of inherited pathology frequencies were determined for the cases of normal distribution with zero mathematical expectancy and constant dispersion of casual environmental influence. Given is the algorithm of dynamic model construction on frequencies of inherited pathology, using experimental data and on the basis of determination of permissible intervals for their prognostic values.

Bayes Theorem↗

PubMed1993

Routine tests of renal function, alcoholism, and nutrition improve the prognostic accuracy of Child-Pugh score in nonbleeding advanced cirrhotics.

In an attempt to improve the prognostic capacity of Child-Pugh score in nonbleeding cirrhotics, 110 consecutive in-patients without gastrointestinal hemorrhage at admission were studied and followed up for 24 months or until death. Fifty-five of the 110 patients (50%) died during this period. Mean survival time was 18.8 +/- 1.4 months (mean +/- SEM). In addition to Child-Pugh score, eight variables, including anthropometric nutritional parameters, routine renal function tests, and alcoholism markers, were recorded at admission. The ability of these variables to improve the prognostic capacity of the Child-Pugh score was assessed with the proportional hazard Cox's regression procedure, using a stepwise method for covariate selection, after including the Child-Pugh score at the first step. Thus, in addition to Child-Pugh score (beta = 0.302), three variables were included in the final model: serum urea (beta = 0.113), MCV (beta = 0.027), and mid-arm muscle circumference (beta = -0.025). According to the contribution of each of these factors to the model, a prognostic index was obtained to estimate survival in the individual patient. An assessment of the predictive power of the model was made by means of a split-sample technique. The prognostic index described in this study may contribute to improve the selection of nonbleeding patients with advanced cirrhosis to receive specific therapies such as transplantation. However, its true clinical relevance will be established only by prospectively comparing its prognostic value with that of the Child-Pugh score in a new sample of patients.

Alcohol Drinking↗

PubMed1996

Prognostic factors and a predictive model of follicular lymphoma: a 25-year study at a single institution in Japan.

The incidence of follicular lymphoma in Japan is far lower than that in western countries, and no large-scale clinicopathologic studies on this neoplasm have been conducted in Japan. We reviewed histopathological specimens from 118 of 135 patients who had been diagnosed as having follicular lymphoma between 1968 and 1993. Prognostic factors influencing survival were analyzed using univariate and multivariate analyses. Factors that were independently significant upon multivariate analysis were incorporated into a predictive model. Ninety-three patients (78.8%) had a confirmed diagnosis of follicular lymphoma. Twenty-one of the remaining 25 patients were categorized as having other lymphoma subtypes, and four patients showed indefinite findings or those suggesting diseases other than lymphoma. Major characteristics of the 93 patients with follicular lymphoma were a median age of 53 years (20-85); 59 males (63%) and 34 females (37%); small cleaved cell type in 33 (35%), mixed cell type in 41 (44%) and large cell type in 19 (20%); stage I/II in 41 (44%) and stage III/IV in 50 (54%). Overall survival was 71% at 5 years, 58% at 10 years, and 43% at 15 years with a median survival of 13.3 years. Multivariate analysis revealed that two variables, age (>60) (P=0.001) and the serum LDH level (>1 x normal value) (P=0.026), were unfavorably significant prognostic factors influencing survival. The predictive model using these two variables identified three risk groups with estimated five-year survival rates of 88.5%, 56.8%, and 31.5%. Age and serum LDH were significant predictors of survival in Japanese patients with follicular lymphoma. Our predictive model may provide a basis for future therapeutic trials against follicular lymphoma in Japan.

Adult↗

PubMed1995

Calculation of biliary atresia prognostic index using a multivariate linear model.

The purpose of this study was to determine the relative value of liver function markers in predicting the magnitude of morbidity and to develop a quantitative estimate of the prognostic risk using a multivariate regression model in patients who have been operated on for biliary atresia. The study sample consisted of 37 patients who had undergone a Kasai portoenterostomy; the jaundice disappeared in 32 and persisted in five. A computer-based stepwise regression procedure produced the linear predictive models by the equation: biliary atresia prognostic index (BAPI) = 9.2 Cu:Zn + 1.0 ZTT + 3.2 TB - 0.05 ChE + 9.9 for infants under 1 year of age, and BAPI = 10.3 Cu:Zn + 0.8 ZTT + 0.03 GGTP - 0.12 ChE + 25.6 for children over 1 year of age. In validation of these models, the indexes fluctuated from -17 to 122, and the degree of morbidity increased linearly with the increase in BAPI. Postoperatively the patients were classified into four categories according to the dynamics of their postoperative course: A (BAPI < 25), successful cases that should not require liver transplantation (40.5%); B (25 < or = BAPI < or = 50), improved cases that have extended survival with their native liver (29.7%); C (50 < BAPI < or = 75), cases that improved in terms of disappearance of jaundice but ultimately will require liver transplantation (8.1%); and D (BAPI > 75), cases that require early referral for transplantation (21.6%). (The percentages indicate the distribution rate of patients at the time of final follow-up evaluation.) These models allow quantification of the risk of morbidity from progressive liver cirrhosis in the individual patient, permitting the clinician to consider whether such patients should be considered for liver transplantation.

Biliary Atresia↗

PubMed2025

Identification and validation of prognostic genes associated with mitochondrial nuclear genes in gastric cancer.

Mitochondrial-related nuclear genes (MNGs) have shown great importance in cancer diagnosis and prognosis, but their role in gastric cancer (GC) remains unclear. GC-related transcriptome data from the gene expression omnibus and cancer genome atlas databases were analyzed to identify differentially expressed MNGs. A prognostic risk model was constructed through univariate Cox and least absolute shrinkage and selection operator regression, validated by Kaplan-Meier (K-M) survival curve and receiver operating characteristic curve. This was followed by immune infiltration analysis, independent prognostic analysis, functional enrichment analysis, drug sensitivity analysis, drug prediction, molecular docking and construction of regulatory networks. Three prognostic genes (ATP8A2, COX15 and TARS2) were identified. The expression of TARS2 and COX15 was positively correlated with CNV, while ATP8A2 was unaffected. The risk model and nomogram, integrating risk score and clinicopathological factors, exhibited excellent predictive performance. A significant correlation was observed between prognostic genes and differential immune cells, such as T cells, B cells, and NK cells. BMS-754807, Gefitinib, JQ1, Lapatinib, and Sapitinib exhibited significant differences in sensitivity between the high-risk group and the low-risk group. The results of molecular docking showed TP8A2 has stable binding ability with cytosine, COX15 with indomethacin, and TARS2 with bisacodyl. RT-qPCR revealed downregulation of ATP8A2 and upregulation of COX15 and TARS2 in GC samples. MNGs, including ATP8A2, COX15, and TARS2, demonstrated significant associations with immune infiltration, CNV, and prognostic outcomes of GC.

Humans↗

PubMed2005

[Allogeneic hematopoietic stem cell transplantation for treatment of Philadelphia chromosome positive acute lymphoblastic leukemia].

OBJECTIVE: To explore the optimal time of allogeneic hematopoietic stem cell transplantation (allo-HSCT) applied in patients with Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph+ ALL), and the optimum order of donor selection. METHODS: From Mar 2000 to Jul 2004, 32 patients with Ph+ ALL were treated by Allo-HSCT, and the follow up ended at Dec 30.2004 with medium of 13 months. Of whom, 24 were male, and 8 were female. Twenty-three patients have been transplanted in CR1, 9 patients beyond CR1 (1 in CR2, 8 in refractory or relapse status). Twelve cases received HSCT from identical sibling donor, 4 unrelated Cord Blood Transplantation (CBT), 3 HSCT from matched unrelated donor (MUD), and 13 HSCT from mismatched related donor (MMRD), of which, 6 cases were M(BCR/ABL) subtype, and 20 m(BCR/ABL) subtype. The Kaplan-Meier method was used to estimate the probabilities of leukemia-free survival (LFS), overall survival (OS) and relapse incidence (RI), and the factors were compared by means of the Log-rank test. Simultaneous effect of multiple covariates were estimated with Cox model. RESULTS: Of all the 32 cases engrafted, 4-year OS was 57.19%, LFS 37.09%, and RI 56.36%. In univariate prognostic analysis model, the OS was higher in CR1 group pre-HSCT than that in non-CR1 group (74.50% vs 22.22%, P=0.0046), LFS was higher (49.06% vs 11.11%, P=0.0057), RI was lower (44.80% vs 84.76%, P=0.0157); the OS was higher in M(BCR/ABL) group than that in m(BCR/ABL) group (100% vs 40.91%, P=0.0318), LFS was higher (75% vs 17.72%, P=0.0057), RI was lower (25% vs 77.88, P=0.0116); OS was similar in HLA MM RD group to that in HLA identical group (52.65% vs 55.56%, P=0.6247), LFS was similar (45.12% vs 30.00%, P=0.8315), and RI was also similar (50.77% vs 60.62%, P=0.8217). In multiple covariate analysis model, the BCR/ABL type was the risk factor of LFS [P=0.005, Exp(B)=9.971] and RI (P=0.006, Exp(B)=9.488), the status of disease pre-HSCT and BCR/ABL subtype was the risk factor of OS [P was 0.010 and 0.038, Exp(B) was 4.532 and 37.537 respectively]. CONCLUSION: We had better do HSCT in CR1 to treat Ph+ ALL, if patient is refractory to chemotherapy, we can try STI571, and HSCT should be done as soon as possible if the patients get CR. Mismatched related donor is considered as regular donor for Ph+ ALL patients without identical donors. We should pay more attention to monitoring and prophylaxis of relapse in m(BCR/ABL) patients after HSCT.

Adolescent↗

PubMed1998

[Mathematical model for the predictive value of a test in critically ill patients studies according to APACHE II score and pathology at admission].

OBJECTIVE: To find a predictive model for mortality at four different days from the admission for critically ill patients. DESIGN: Retrospective study on two consecutive series of critically ill patients admitted in ICU. SUBJECTS: 1254 critically ill patients, subdivided into two series of 813 (561 survivors and 252 non survivors) and 441 patients (291 survivors and 150 non survivors), respectively. INTERVENTIONS: None. MEASUREMENTS: All patients had APACHE II calculated within the first 24 hours from the admission in ICU and, if the patient was still in ICU, also at the 5th, 10th and 15th day from the admission. Casistics was subdivided into two unequal series, ratio 2:1, with a random selection made on each of the 6 considered years. On the 1st series, in 1st, 5th, 10th and 15th day, for mathematical predictive models were made, using stepwise logistic regression (BMDP, Los Angeles). In the 1st day the following independent variables were utilized: APACHE II score, the specific diagnosis at admission, fitted following Knaus' diagnostic criteria, united in 6 principal categories, while for the other 3 days the variation % of APACE II score as regards the previous day. RESULTS: For each of the considered day four mathematical models have been made. These models have been validated in both series in calibration from the Hosmer-Lemeshow Goodness-of-fit test and in discrimination from the ROC curves. For each day Y (Prob.% to die) = eLogit/1 + eLogit, where Logit = beta 0 (constant) + beta 1*APACHE II + beta 2*Variat.%APACE II (difference between actual APACHE II - APACHE II of the previous day/actual APACHE II) + beta k, (coefficient pertinent to pathology). CONCLUSIONS: The mathematical model, as other models do, stratifies enough the casistics according to the risk of death. Waiting for further studies to make more precise prognostic mathematical models, this one and others can help the clinical assessment in single patient evaluation.

APACHE↗

PubMed2005

Predictive survival model with time-dependent prognostic factors: development of computer-aided SAS Macro program.

AIMS AND OBJECTIVES: Computer program for the prediction of survival with respect to time-dependent proportional hazards regression model has been rarely addressed. We therefore developed a SAS Macro program for time-dependent Cox regression predictive model for empirical survival data associated with time-dependent covariates. METHOD: Time-dependent proportional hazards regression model and partial likelihood in association with time-varying predictors were explicitly delineated. Baseline hazard using Andersen's method was incorporated into proportional hazards regression model to predict the dynamic change of cumulative survival in respect of time-varying predictors. Two SAS Macro programs for time-dependent predictive survival model and model validation using receiver operative characteristics were written with SAS IML language. RESULTS: The computer program was applied to data on clinical surveillance of small hepatocellular carcinoma (HCC) treated by percutaneous ethanol injection (PEI) or transcatheter arterial embolization (TAE) with time-varying predictors such as alpha-feto protein (AFP) and other biological markers. CONCLUSION: The program is very useful for real-time prediction of cumulative survival on the basis of time-dependent covariates.

Carcinoma, Hepatocellular↗

PubMedDate not supplied

Indications for paraaortic lymph node dissection in gastric cancer patients with paraaortic lymph node involvement.

BACKGROUND/AIMS: The surgical results for stage IVb gastric cancer remain very poor. The purpose of the current study is to reveal indications for paraaortic lymph node dissection in stage IVb gastric cancer patients with paraaortic lymph node involvement by analyzing prognostic factors for 3-year survival of stage IVb gastric cancer patients followed by curative B resection. METHODOLOGY: The 3-year survival in clinicopathologic variables were compared by univariate analysis. Using Cox proportional hazards regression model, independent prognostic factors were identified from 11 variables. RESULTS: Overall 5-year survival in stage IVb was 26.5%; mean survival was 19 months. Using univariate analysis, p53 expression significantly influenced 3-year survival. Using Cox proportional hazards regression model, the number of total positive lymph nodes, the number of positive paraaortic lymph nodes, and p53 expression were independent prognostic factors. CONCLUSIONS: In stage IVb, paraaortic lymph node dissection should be indicated in patients with < or = 10 total positive lymph nodes, and < or = 3 positive paraaortic lymph nodes or p53 expression < or = 50%. This indication can be applied according to the preoperative imaging, the staining of p53 by endoscopic biopsy specimens and the intraoperative microscopic evaluation of dissected lymph nodes.

Adult↗

PubMed2001

Modeling the long-term frequency distribution of regional ozone concentrations using synthetic meteorology.

A new method is developed to generate the meteorological input fields required for use with photochemical airshed models that seek to predict the effect of pollutant emissions on the long-term frequency distribution of peak O3 concentrations. Instead of using meteorological fields derived from interpolation of direct weather observations, this method uses synthetically generated meteorological data. These synthetic meteorological fields are created by first constructing a semi-Markov process that generates a time series of large-scale synoptic weather conditions that statistically resemble the occurrence and persistence of synoptic weather patterns during specific months of the year. Then for each day within each synoptic weather category, local weather variables indicative of the meteorological potential for ozone formation are drawn from the approximated joint distribution of the summation of three pressure gradients across the airshed and the 850 mb temperature measured in the early morning. The synthetic initial conditions are combined with boundary values that are extracted from historical days that match the chosen synoptic class, temperature, and pressure gradient values as closely as possible for use in a prognostic mesoscale meteorological model. The prognostic mesoscale meteorological model generates the meteorological input fields necessary for the photochemical airshed model. The airshed model driven by synthetically generated meteorological data is executed for a 31 day period that statistically resembles weather during the month of August in Southern California using pollutant emissions data from the year 1987. The procedure produced a frequency of occurrence of peak 8 h average ozone concentrations that compared well both to that produced by the deterministic model as well as to the O3 concentrations observed over the August months of the years 1984-1990.

Air Pollutants↗

PubMed1994

[Grouped Cox regression model and its application in study of prognostic factors on cancer].

Cox proportional hazards regression model is the most popular multivariate regression model for analysis of survival data in medical follow-up studies and clinical trials, but it is unable to handle grouped survival data or large data sets with many tied failure times adequately. This paper explores the grouped proportional hazards regression model (GPH model) and its use in analysis of large data sets presented in life tables. By use of the data in a lung cancer follow-up study conducted in urban area of Shanghai, the authors give an example in detail for analysing prognostic factors of lung cancer by using GLIM.

Adult↗

PubMed1992

DNA level and stereologic estimates of nuclear volume in squamous cell carcinomas of the uterine cervix. A comparative study with analysis of prognostic impact.

Grading of malignancy in squamous cell carcinomas of the uterine cervix is based on qualitative, morphologic examination and suffers from poor reproducibility. Using modern stereology, unbiased estimates of the three-dimensional, volume-weighted mean nuclear volume (nuclear vv), were obtained in pretreatment biopsies from 51 patients treated for cervical cancer in clinical Stages I through III (mean age of 56 years, follow-up period greater than 5 years). In addition, conventional, two-dimensional morphometric estimates of nuclear and mitotic features were obtained. DNA indices (DI) were estimated by flow cytometry. Finally, the semiquantitative malignancy grade score value (MGS) was determined according to previously published methods. Estimates of nuclear vv were on average increased in euploid lesions (2P = 0.01), but the overall relationship between nuclear vv and DI was poor. Different clinical stages of disease did not differ with regard to nuclear vv (2P = 0.99) and DI (2P = 0.56). No relationship was disclosed between MGS and nuclear vv (2P = 0.85). Single-factor analysis showed prognostic impact of clinical stage of disease (2P = 0.0001) and DI (2P = 0.04), whereas estimates of nuclear vv were only of marginal prognostic significance (2P = 0.07). However, Cox multivariate regression analysis showed independent prognostic value of patient age and nuclear vv along with clinical stage and DI. All other investigated variables were rejected from the model. A prognostic index with highly distinguishing capacity between prognostically poor and favorable cases was constructed (2P = 1.9 x 10(-7)). It is concluded that realistic estimates of nuclear volume are independent of nuclear DNA content and are of prognostic value for objective malignancy grading in patients with squamous cell carcinoma of the uterine cervix.

Adult↗