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PubMed2026

Identification and evaluation of glutamine-related gene characteristics based on multi-omics to predict the prognosis of patients with colorectal cancer.

BACKGROUND: Colorectal cancer (CRC), a prevalent malignancy of the gastrointestinal tract, ranks among the leading causes of cancer-related morbidity and mortality. Its clinical course is marked by high fatality and poor prognosis. Elucidating the mechanisms underlying CRC initiation and recurrence is therefore critical for identifying novel therapeutic targets. METHODS: This study incorporated two datasets, TCGA-CRC and GSE17537. A total of 84 glutamine metabolism-related genes (GMRGs) were identified, and differential expression analysis was conducted using the TCGA-CRC dataset. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to determine gene modules most strongly associated with GMRG scores. Single-cell RNA sequencing (scRNA-seq) was utilized to characterize key cellular clusters and to identify differentially expressed genes (DEGs) between high and low glutamine metabolism (GM) groups. Overlapping GMRGs were visualized using the ggVennDiagram package in R. A CRC risk prediction model was developed through Cox proportional hazards and LASSO regression analyses, with performance evaluated by ROC curves. Cell type enrichment across 64 immune and stromal populations was assessed via xCell, and intergroup differences were tested using the Wilcoxon rank-sum test. TIDE scores were used to estimate immunotherapy responsiveness, while oncoPredict facilitated drug sensitivity profiling. PCOLCE2 expression in CRC was validated by RT-qPCR and Western blotting. Its functional role was examined through CCK-8 assays, invasion and migration tests, flow cytometry, and glutamate quantification. RESULTS: ScRNA-seq analysis identified two key cell populations and 437 DEGs associated with GM status. WGCNA pinpointed the MEgreen module as most significantly correlated with GMRG scores, encompassing 1075 genes. Integration of DEGs, module genes, and GM-related DEGs yielded 60 candidate genes for downstream analysis. A GMRG-based prognostic model comprising six genes (SRPX, CXCL1, GPX3, PCOLCE2, CLU, SEMA3E) demonstrated strong predictive performance. Prognostic gene expression correlated with immune and stromal infiltration patterns, as indicated by Spearman correlation analysis. The high-risk group exhibited diminished predicted response to immunotherapy (TIDE scores). Drug sensitivity analysis identified four compounds—Dasatinib-51, WH-4-023-56, TWS-119-366, and LDN-193189-478—with elevated efficacy in high-risk CRC cases. PCOLCE2 expression was significantly reduced in CRC tissues. Functional assays revealed that PCOLCE2 knockdown did not substantially affect cell proliferation but significantly impaired invasion and migration in CRC cells, increased apoptosis, and suppressed both glutamine uptake and glutamate production—highlighting its oncogenic role. CONCLUSION: Six GMRGs—SRPX, CXCL1, GPX3, PCOLCE2, CLU, and SEMA3E—were identified as key components of a robust prognostic model for CRC. These findings offer valuable insights into CRC pathogenesis and potential therapeutic strategies. Notably, this study provides the first evidence implicating PCOLCE2 as a tumor-promoting factor in CRC.

Glutamine↗

PubMed2006

The role of adjuvant therapy in non-metastatic RCC.

Renal cell carcinoma (RCC) presents as localized disease in 54% of the cases. For these patients, surgery is the primary curative treatment. Unfortunately, up to 65% of all patients show recurrent disease. For metastatic RCC non-specific immunotherapy is currently the treatment of choice. Nevertheless, several new modalities, e.g. WX-G250, oncophage and anti-angiogenic compounds like sunitinib and sorafenib are being explored with favorable results. Still, their place in the primary treatment of advanced RCC has yet to be determined. Because of the high percentage of recurrent disease, there is a need to identify these patients with conventional and molecular risk factors. Furthermore, adjuvant therapy to reduce risk of recurrence of RCC following nephrectomy is of clinical relevance. A review of recent literature was performed on the topics prognostic models, risk factors and adjuvant treatment for non-metastasized RCC. Combining classical risk factors for progression of RCC has shown to be effective for stratifying patients into risk groups. The UCLA integrated staging system (UISS) is the currently the only validated prognostic model. Whether molecular markers are able to better identify high-risk patients is still under investigation. Adjuvant therapy has been explored in the treatment for RCC and the use of non-specific cytokine regimens has so far not shown to be effective in the adjuvant setting. More specific therapies, e.g. WX-G250, oncophage and anti-angiogenic drugs are clinically active in patients with advanced RCC. Large randomized clinical trials with these drugs are currently ongoing to evaluate their effect in patients with localized RCC.

Carcinoma, Renal Cell↗

PubMed2005

Improving trial power through use of prognosis-adjusted end points.

BACKGROUND AND PURPOSE: The stroke patient population is heterogeneous, leading to wide variation in outcome caused by differences in age, initial severity, and presence of concomitant disease. Setting an identical recovery target for all patients in intervention trials may conceal individually important therapeutic treatment effects. Instead, a variable end point that takes severity or likely prognosis into account may be more informative. METHODS: We used data from the Glycine Antagonist in Neuroprotection (GAIN) International trial to assess statistical power of various primary end points for intervention trials. We selected prognosis-adjusted cut points based on Barthel Index (BI) or Rankin Scale (RS) using a prognostic model, or assigned a fixed end point within subgroups of patients defined by their Oxford category or National Institutes of Health Stroke Scale (NIHSS) score. We simulated a treatment effect and estimated statistical power with standard formulae. RESULTS: Assignment of end points using a prognostic model for individual patients increased statistical power, when compared with assigning end points using only the Oxford classification. For the BI, power was increased from 60% to 88% (equivalent to a 49% reduction in sample size if power remains unchanged). With the RS end points, power was increased from 84% to 92% (or a 24% reduction in sample size). Versus a fixed end point for all patients, model-based methods increased power by 22 percentage points for BI> or =95 and 14 percentage points for RS< or =1 (effective sample size reductions 43% and 34%). CONCLUSIONS: Prognosis-adjusted end points can increase statistical power compared with fixed end points. Assessment is based on realistic goals for individual patients and yet trial results remain generalizable.

Age Factors↗

PubMed2026

Identification of ultrasound-associated gene candidates in myeloid cells and construction of a prognostic risk model for acute myeloid leukemia.

BACKGROUND: Incorporating ultrasound (US) treatment sensitivity analysis may improve the treatment of acute myeloid leukemia (AML). METHODS: This study integrated single-cell and bulk datasets for analysis. Differential expression analysis between US-treated and control samples was performed using limma package. The AUCell package was used to calculate US-associated scores in the single-cell dataset. Differentially expressed genes (DEGs) between the specific groups were identified, followed by intersection analysis with previously identified DEGs. Univariate regression, Least Absolute Shrinkage and Selection Operator (LASSO) analysis (using the glmnet package), and stepwise multivariate regression (using the MASS package) were used to refine the candidate genes and to construct a risk model. The model genes were validated using in vitro experiments. Enrichment analysis was conducted using gene set enrichment analysis (GSEA), and immune infiltration was evaluate by single-sample GSEA (ssGSEA) and ESTIMATE algorithms. The correlations between RiskScores and drug sensitivity were analyzed by oncoPredict package. Finally, tumor mutational burden (TMB) and genomic mutations were compared between the risk groups. RESULTS: Nine prognostic signatures (SPINK2, HNRNPAB, SH3BGRL3, CLEC11A, ITGA4, RPL39L, MX1, HEXIM1, and MAP4K4) were identified. Particularly, low expression of SPINK2 attenuated the activity and invasion of AML cells. High-risk group had higher immune cell infiltration. Eight drugs were predicted to be correlated with the RiskScore model. DNMT3A and RUNX1 showed higher mutation frequencies in the high-risk group, whereas KIT and MUC16 showed higher mutation frequencies in the low-risk group. CONCLUSION: The RiskScore model established in this study provides a theoretical basis for clinically screening responsive populations and optimizing treatment strategies.

Humans↗

PubMed1997

Hepatocellular carcinoma in primary biliary cirrhosis and its impact on outcomes.

In this study we have determined the incidence of hepatocellular carcinoma (HCC) development in primary biliary cirrhosis (PBC) and its effects on patient survival. Six hundred and sixty seven patients with liver histology compatible with or diagnostic of PBC were seen over a 20-year period. Two hundred and seventy three patients who had stage III or IV disease on their last biopsy and who had been followed up for at least 1 year following that biopsy (total follow-up with advanced disease 2,010 patient years) were identified (243 female, 30 male). Patients who developed HCC were identified and their confounding risk factors were excluded. Mayo risk scores were calculated for each clinic attendance and expected survival for each time point was compared with subsequent actual survival. Sixteen cases of HCC were seen in the patients with stage III or IV disease on last biopsy, providing an overall incidence of 5.9% in this group. Fourteen of these patients had died of HCC related causes, and 2 patients were alive at the census point. The incidence of HCC was significantly higher in males with stage III/IV disease than in females (20% vs. 4.1%, P < .005). Nine of one hundred and eight (8.3%) total female deaths in this group was attributable to HCC compared with 5 of 11 (45.5%, P < .05) male deaths. HCC was not seen in any of the 394 patients with stage I and II PBC followed-up over the same time period. Throughout the disease course of all PBC patients with HCC, the Mayo prognostic model over-predicted survival. Whereas it is a relatively rare complication of cirrhotic PBC in women, HCC is a relatively common cause of death in male PBC patients with cirrhosis. HCC typically develops several years after the onset of cirrhosis, and is poorly predicted by prognostic models. In view of these findings, consideration should be given to careful screening for HCC in male PBC patients with cirrhosis. The risk of HCC development may be an additional reason to consider earlier transplantation in these patients.

Aged↗

PubMed2004

A randomized controlled trial of colchicine plus ursodiol versus methotrexate plus ursodiol in primary biliary cirrhosis: ten-year results.

Primary biliary cirrhosis frequently progresses despite treatment with ursodeoxycholic acid (UDCA), the only approved therapy. Previous studies suggested that colchicine and methotrexate may improve biochemical tests of liver function, symptoms, and liver histology. The aim of the present study was to determine if the addition of colchicine or methotrexate to UDCA would improve survival free of liver transplantation. Eighty-five patients with histologically confirmed primary biliary cirrhosis whose serum alkaline phosphatase levels were at least twice the normal level and who were not yet candidates for liver transplantation were randomly assigned to receive colchicine or methotrexate in a double-blind study. UDCA was administered to all patients after 2 years. The primary end point was survival free of liver transplantation. Patients were followed up for a total of up to 10 years or until treatment failure. Data were analyzed on an intention-to-treat basis. Transplant-free survival was similar in both groups: 0.57 for colchicine plus UDCA and 0.44 for methotrexate plus UDCA, results that are similar to those predicted by the Mayo prognostic model. Significant improvement in liver biochemical tests and liver histology was observed in a subset of patients in both treatment groups who remained in the study for all 10 years. In conclusion, neither colchcine plus UDCA nor methotrexate plus UDCA improved survival beyond that predicted by the Mayo prognostic model. However, clinical, histologic, and biochemical improvement observed among those who remained in the study for 10 years suggests a possible benefit of these drugs in a subset of patients.

Anti-Inflammatory Agents↗

PubMed2005

Mortality risk factors and validation of severity scoring systems in critically ill patients with acute renal failure.

BACKGROUND: Risk stratification and prediction of outcome in acute renal failure patients in the intensive care unit are important determinants for improvement of patient care and design of clinical trials. METHODS: In order to identify mortality risks factors and validate general and specific predictive models for acute renal failure (ARF) patients in the intensive care unit (ICU), 324 patients were prospectively evaluated. Multivariate analysis by logistic regression was utilized for identification of mortality risk factors. Discrimination and calibration were used to evaluate the performance of the following models at referral to nephrologist and at initiation of renal replacement therapy: APACHE II, SAPS II, LODS, and ATN-ISI. Organ failure was assessed by SOFA and OSF. RESULTS: The hospital mortality rate was 85%. The identified mortality risk factors were: age > or = 65 yr, BUN > or = 70 mg/dL, ARF of septic origin, and previous hypertension. Serum creatinine > or = 3.5 mg/dL, systolic blood pressure > or = 100 mm Hg, and normal consciousness were associated with mortality risk reduction. Performance of all prognostic models was disappointing with unsatisfactory calibration and underestimation of mortality on the day of referral to the nephrologist and at initiation of renal replacement therapy. CONCLUSIONS: Cross-validation of prognostic models for ARF resulted in poor performance of all studied scores. Therefore, a specific model is still warranted for the design of clinical trials, comparison of studies, and for prediction of outcome in ARF patients, especially in the ICU.

APACHE↗

PubMed1997

Character of the invasive margin in colorectal cancer: does it improve prognostic information of Dukes staging?

PURPOSE: The clinical significance and prognostic value of the histopathologic parameters used in both the Dukes and Jass classifications were evaluated to select those with an independent effect on survival after radical surgery for colorectal cancer. METHODS: The depth of local spread (limited to the bowel wall or extended beyond it), the number of metastatic lymph nodes (none, 1-4, more than 4), the character of the invasive margin (pushing or infiltrating), and the presence or absence of conspicuous peritumoral lymphocytic infiltration were assessed in 235 patients who had undergone radical resection for colorectal cancer. The influence of these variables on survival was studied by univariate and multivariate analysis. RESULTS: No significant difference in survival was found between patients with conspicuous peritumoral infiltrate and those without it; moreover, multivariate analysis failed to show any independent prognostic value for either lymphocytic infiltration or depth of local invasion. However, the character of the invasive margin and the number of metastatic lymph nodes were identified as the only variables with any independent importance on survival. Based on these data, a new prognostic model may be proposed; it uses the character of the infiltrative margin as a discriminating factor among patients within the lymph node-negative (Dukes A and B stages) and lymph node-positive (Dukes C1 and C2 subsets) groups. A good prognosis for Dukes A, B, and C1 patients was associated with pushing tumors; C1 and C2 patients with infiltrating tumors had a poor prognosis. On the whole, the new prognostic model has allowed for the placement of 59.6 percent of our patients into groups that provide a confident prognosis. The clinical outcome of Dukes A and B patients with infiltrating tumors is still uncertain. CONCLUSIONS: The character of the invasive margin is an important prognostic factor in colorectal cancer. The association of this parameter with the traditional Dukes classification may provide additional useful prognostic information and aid in the selection of those patients who could most benefit from adjuvant therapy.

Adenocarcinoma↗

PubMed2026

A three-gene radioresistance signature predicts tumor progression in cervical cancer.

BACKGROUND: As a primary curative treatment for locally advanced cervical cancer, radiotherapy is frequently undermined by radioresistant tumor cells that evade cell death and subsequently drive post-treatment tumor progression. This study aimed to identify candidate genes associated with radioresistance in cervical cancer and to explore their potential in predicting unfavorable outcomes among radioresistant patients, thereby providing a reference for future research. METHODS: We screened for co-expressed genes using transcriptomic data from radiation non-complete response (NCR) cervical cancer patients in Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Cox regression analyses were conducted to identify the most significant radioresistance-associated genes for constructing a prognostic model. The predictive performance of this model was further validated through logistic regression, weighted gene co-expression network analysis (WGCNA), and pan-cancer analyses. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) was performed to quantify the expression levels of key genes in cervical cancer tissue samples from radiosensitive and radioresistant patients. RESULTS: The resulting prognostic model comprised three genes: MTMR11, VANGL1, and CD46. This gene panel was significantly associated with the prognosis of cervical cancer patients receiving radiotherapy and showed acceptable predictive performance across multiple cancer types. qRT-PCR analysis revealed that the expression patterns of MTMR11 and VANGL1 were generally consistent with radioresistance of cervical cancer, whereas CD46 exhibited an unexpected expression trend. CONCLUSIONS: Our findings indicate that MTMR11, VANGL1, and CD46 are associated with radioresistance and prognosis in cervical cancer. Their potential clinical utility, especially in predicting radiotherapy response at the individual patient level, requires further validation in larger, independent, and prospective cohorts.

Cervical cancer↗

PubMed1994

Levels in the follow-up of a long-term clinical process.

I developed a 5-stage, 7-compartment prognostic model for the long-term follow-up of 28 patients with sickle chronic lung disease. Estimated hazard functions for transition varied with Stage 1, 2, 3, or 4 sickle chronic lung disease as well as with stage at diagnosis and duration of observation with hematologic disease before the recognition of sickle chronic lung disease. Individualized hazard matrices produced 28 prognostic probability functions of time that had heterogeneous levels and shapes. The probability of death from the time of diagnosis to the end of each patient's period of follow-up determined that patient's prognostic integrated hazard. Such integrated hazard values, developed from a prognostic model, provide a superior context for carrying out standard formal tests and inferences regarding the effects of alternative treatments in randomized clinical trials.

Adolescent↗

PubMed2004

Laminin, Her2/neu and Ki-67 as prognostic factors in non-small cell lung cancer.

PURPOSE: The aim of this study was to determine the values of Ki-67 antigen, oncoprotein Her2/neu and laminin, as prognostic and predictive factors in NSCLC, and on the basis of these markers to create a prognostic model which would make it possible to identify patients with a high risk of disease recurrence. MATERIAL AND METHODS: The material for the study came from 64 patients with NSCLC, who underwent surgery in Dolnoślaskie Centrum Gruźlicy i Chorób Płuc i 1996-2000, and subsequently were given radiation therapy in Dolnoślaskie Centrum Onkologii. RESULTS: Among the markers researched, a high level of (intracellular) laminin in carcinoma cells was found to be an unfavourable prognostic factor. Also, another group of patients with an overexpression of oncoprotein Her2/neu were found to have a poorer prognosis, although the influence of proliferative index Ki-67 on patient survival could not be explained. The prognostic model LAMHER, which was defined on the basis of the intracellular laminin level and expression HER2/neu, enables the identification of a group of patients with a high risk of disease recurrence. In a multidimensional analysis of the "classification tree", it was found that patients with the highest risk of disease recurrence were those with LAMHER = 1 (overexpression Her2/neu and/or a high level of intracellular laminin), and patients with LAMHER = 0 but a Fractionation Dilution Factor higher than 1.57. CONCLUSIONS: The conclusion of this study is that multiple molecular marker testing is necessary to detect an independent prognostic impact on survival and is therefore superior to single marker testing. Based on LAMHER testing, two groups of patients could be defined: a low-risk group (LAMHER = 0) and a high-risk group (LAMHER = 1) for failure of standardized treatment.

Biomarkers, Tumor↗

PubMed2005

The application of special technologies in diagnostic anatomic pathology: is it consistent with the principles of evidence-based medicine?

Proponents of evidence-based medicine (EBM) have emphasized the need to consider the quality of different sources of medical information and have proposed various methods to integrate available "best evidence" into rules, guidelines and other diagnostic, therapeutic and prognostic models. The various factors that can affect the internal validity of studies in anatomic pathology, such as interobserver variability, use of retrospective rather than prospective data and others, are reviewed. The need for testing for the external validity of the results of anatomic pathology studies is introduced, using "test sets" of cases that have not been used to generate the classification or prognostic models. This methodology has been seldom used in anatomic pathology to validate the generalizability of various "entities," usefulness of diagnostic tests under different conditions and other information. Basic concepts of meta-analysis for research synthesis are introduced; these methods have been seldom used in anatomic pathology to integrate information from different studies using quantitative techniques rather than summary tables that merely list the results of various publications. The potential use of decision analysis and value of information analysis for the adoption of new tests is briefly discussed.

Data Interpretation, Statistical↗

PubMed2005

Long-term prognosis of acute otitis media in infancy: determinants of recurrent acute otitis media and persistent middle ear effusion.

OBJECTIVES: Children under 2 years of age with acute otitis media are known to have a relatively poor prognosis. The objective of this study was to assess whether known determinants for recurrent acute otitis media and persistent middle ear effusion after an episode of acute otitis media during childhood also apply to children under 2 years. METHODS STUDY DESIGN: prospective study of 210 children under 2, with identification of potential prognostic determinants. Univariate and multivariate logistic regression analyses were applied to evaluate which parameters independently contributed to the prediction of both outcome measures (recurrent acute otitis media and persistent middle ear effusion). A prognostic function was developed, and the area under the receiving operating characteristic (ROC) was used to estimate the predictive ability of the prognostic models. POPULATION: children under 2 years of age with an episode of acute otitis media in family practice. OUTCOMES MEASURED: recurrent acute otitis media and persistent middle ear effusion. RESULTS: For the outcome recurrent acute otitis media data from 210 children were used and winter season, male sex, passive smoking and persistent symptoms for more than 10 days at presentation were independent prognostic determinants. For the outcome persistent middle ear effusion data from 190 children were used and winter season, bilateral disease at entry, a sibling history of recurrent acute otitis media, and a previous episode of acute otitis media independently predicted the outcome. No sufficiently discriminatory prognostic model could be constructed for either outcome measure. CONCLUSION: Prediction of recurrent acute otitis media or persistent middle ear effusion in individual young children remains poor.

Acute Disease↗

PubMed2005

Prediction of appropriate timing of palliative care for older adults with non-malignant life-threatening disease: a systematic review.

BACKGROUND: most people in contemporary western society die of the chronic diseases of old age. Whilst palliative care is appropriate for elderly patients with chronic, non-malignant disease, few of these patients access such care compared with cancer patients. Objective referral criteria based on accurate estimation of survival may facilitate more timely referral of non-cancer patients most appropriate for specialist palliative care. OBJECTIVE: to identify tools and predictor variables that might aid clinicians estimate survival and assess palliative status in non-cancer patients aged 65 years and older. METHODS: systematic review and quality assessment using criteria modified from the literature. RESULTS: 11 studies that evaluated prognoses in hospitalised and community-based older adults with non-malignant disease were identified. Key generic predictors of survival were increased dependency of activities of daily living, presence of comorbidities, poor nutritional status and weight loss, and abnormal vital signs and laboratory values. Disease-specific predictors of survival were identified for dementia, chronic obstructive pulmonary disorder and congestive heart failure. No study evaluated the relationship between survival and palliative status. CONCLUSION: prognostic models that attempt to estimate survival of < or = 6 months in non-cancer patients have generally poor discrimination, reflecting the unpredictable nature of most non-malignant disease. However, a number of generic and disease-specific predictor variables were identified that may help clinicians identify older, non-cancer patients with poor prognoses and palliative care needs. Simple, well-validated prognostic models that provide clinicians with objective measures of palliative status in non-cancer patients are needed. Additionally, research that evaluates the effect of general and specialist palliative care on psychosocial outcomes in non-cancer patients and their carers is needed.

Aged↗

PubMed2001

[Predicting the outcome in severe injuries: an analysis of 2069 patients from the trauma register of the German Society of Traumatology (DGU)].

UNLABELLED: On hospital admission numerous variables are documented from multiple trauma patients. The value of these variables to predict outcome are discussed controversially. The aim was the ability to initially determine the probability of death of multiple trauma patients. Thus, a multivariate probability model was developed based on data obtained from the trauma registry of the Deutsche Gesellschaft für Unfallchirurgie (DGU). PATIENTS AND METHODS: On hospital admission the DGU trauma registry collects more than 30 variables prospectively. In the first step of analysis those variables were selected, that were assumed to be clinical predictors for outcome from literature. In a second step a univariate analysis of these variables was performed. For all primary variables with univariate significance in outcome prediction a multivariate logistic regression was performed in the third step and a multivariate prognostic model was developed. RESULTS: 2069 patients from 20 hospitals were prospectively included in the trauma registry from 01.01.1993-31.12.1997 (age 39 +/- 19 years; 70.0% males; ISS 22 +/- 13; 18.6% lethality). From more than 30 initially documented variables, the age, the GCS, the ISS, the base excess (BE) and the prothrombin time were the most important prognostic factors to predict the probability of death (P(death)). The following prognostic model was developed: P(death) = 1/1 + e(-[k + beta 1(age) + beta 2(GCS) + beta 3(ISS) + beta 4(BE) + beta 5(prothrombin time)]) where: k = -0.1551, beta 1 = 0.0438 with p < 0.0001, beta 2 = -0.2067 with p < 0.0001, beta 3 = 0.0252 with p = 0.0071, beta 4 = -0.0840 with p < 0.0001 and beta 5 = -0.0359 with p < 0.0001. Each of the five variables contributed significantly to the multifactorial model. CONCLUSIONS: These data show that the age, GCS, ISS, base excess and prothrombin time are potentially important predictors to initially identify multiple trauma patients with a high risk of lethality. With the base excess and prothrombin time value, as only variables of this multifactorial model that can be therapeutically influenced, it might be possible to better guide early and aggressive therapy.

Adolescent↗

PubMed1997

Prognostic factors for patients with advanced seminoma treated with platinum-based chemotherapy.

Prognostic factors for 3-year progression-free survival (PFS) were defined in 286 patients with advanced seminoma treated with cisplatin-based chemotherapy at 10 European oncology units (no prior treatment: 236; prior radiotherapy: 50). Previously irradiated patients displayed a 69% PFS as compared to 87% in those presenting with advanced seminoma at the time of diagnosis (P = 0.009). In the univariate analysis, the extent and site of disease before chemotherapy and the level of serum LDH (< 2.0 versus > or = 2.0 x upper limit of normal) correlated with PFS in previously non-irradiated patients, but not in patients with prior radiotherapy. The multivariate analysis was, therefore, restricted to previously non-irradiated patients. The presence of non-pulmonary visceral metastases and a serum LDH level of > or = 2 x normal (N) proved to be independent prognostic factors. Based on these variables, two prognostic models were constructed and validated in an external data set of 166 comparable patients. For clinical use, Model 2 is recommended. The good-prognosis group comprises non-irradiated patients with stage II seminoma and any LDH level at presentation, or stage III and IV patients (with lung metastases only) whose serum LDH level is < 2 x N. These patients display a 94% 3-year PFS. The poor prognosis group includes all other patients with a 56% PFS. With this prognostic model, individualisation of the therapeutic approach may be considered in patients with advanced seminoma and a high risk of chemotherapy-related toxicity.

Adult↗

PubMed1993

How should we identify high risk testicular tumour patients? Round table discussion.

Various prognostic models are used to predict the outcome of testicular tumour patients, and these are usually based on serum tumour marker levels (AFP and hCG), number and size of metastases to para aortic nodes, lungs and supraclavicular nodes. Greater predictive accuracy can be achieved if 'dynamic markers' are used in addition to these pretreatment variables. Dynamic markers are assessed during treatment by examining the rate of tumour marker decline. Prognostic models can subdivide patients into good risk, intermediate risk, and very poor risk groups. Cisplatin may be replaced by the less toxic carboplatin in good risk patients. High dose chemotherapy with autologous bone marrow transplantation should only be considered for very poor risk patients. Prognosis may be worse if the patient is a smoker, or if he has a first degree relative with testicular cancer. New markers such as chromosomal abnormalities or gene mutations should be examined.

Clinical Trials as Topic↗

PubMedDate not supplied

[Discriminant analytic model for prognostic assessment of pregnancies at risk for premature labor].

We examined 114 women with preterm labor using discriminance analysis to assess predictive values in terms of prolongation of gestational age and gestational age at the time of delivery. We used parameters like medical history, clinical features, infections, Doppler sonography and cardiotocography. Maternal temperature, cardiotocographic findings, premature rupture of membranes, number of abortions and pregnancy terminations and cervical dilatation at the time of admission contribute significantly to predict prolongation of pregnancy (< or = as well as > 7 days). Our results from this analysis showed sensitivity and specificity of 0.70 and 0.97 and positive and negative predictive values of 0.89 and 0.91, respectively. We observed significant differences concerning parameters like preterm rupture of membranes, cervical dilatation, pathological bacteria in the vagina and pathological Doppler values between subsequent preterm and term deliveries in pregnancies with a prolongation of > 7 days was. Upon reclassifying our results, we obtained sensitivity and specificity of 0.69 and 0.89 and positive and negative predictive values of 0.78 and 0.84, respectively. Early prognostic assessment of preterm labor can be made with discriminance analysis. The results inspire us to perform a prospective examination of the therapy plan that we have obtained.

Cardiotocography↗