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PubMed2026

Development of m6A-related prognostic models for survival in lung squamous cell carcinoma with different PD-L1 expression levels.

BACKGROUND: Programmed death-ligand 1 (PD-L1) is widely used in the clinical context of immune checkpoint inhibitor therapy, but its relationship with N6-methyladenosine (m6A) RNA methylation in lung squamous cell carcinoma (LUSC) has not been well defined. This study aimed to investigate the association between PD-L1 messenger RNA (mRNA) expression and m6A regulator expression patterns and to develop exploratory m6A-based prognostic models in LUSC. METHODS: Transcriptome data from 502 patients with LUSC were obtained from The Cancer Genome Atlas (TCGA). Patients were divided into PD-L1 high-expression (PHE) and PD-L1 low-expression (PLE) groups according to the median PD-L1 mRNA level. Differential expression and correlation analyses were performed for 30 m6A regulators. Transcriptome sequencing data from surgical specimens from 28 Asian patients with LUSC were used for expression-pattern comparison. Principal component analysis (PCA), univariate Cox regression, and least absolute shrinkage and selection operator (LASSO)-Cox regression were used to construct prognostic models in the TCGA cohort. RESULTS: In the TCGA cohort, the main differentially expressed m6A regulators between the two PD-L1 groups were YTHDF2 (P<0.001), IGF2BP3 (P<0.001), and YTHDC2 (P<0.001). In the Asian cohort, ALKBH5 (P=0.008) and ZC3H13 (P=0.03) showed significant differences. LASSO-Cox models were constructed for the overall LUSC cohort and for the PHE and PLE subgroups. The overall model included METTL3, HNRNPC, and CBLL1, with a 5-year time-dependent area under the receiver operating characteristic curve (AUC) of 0.579. The 5-year AUCs were 0.742 in the PHE subgroup and 0.652 in the PLE subgroup. The risk score remained independently associated with prognosis in multivariate Cox analysis. CONCLUSIONS: In LUSC, PD-L1 mRNA status was associated with distinct m6A regulator expression profiles. In the TCGA cohort, the PHE subgroup showed higher expression of CBLL1, G3BP1, IGF2BP3, FMR1, and YTHDC2, but lower expression of VIRMA, YTHDF2, and PRRC2A compared with the PLE subgroup. In the National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences (CICAMS) cohort, ALKBH5 and ZC3H13 were more highly expressed in the PHE subgroup. Moreover, m6A-based risk models were associated with survival outcomes, with significant prognostic separation in the overall TCGA cohort and the PHE subgroup, whereas the PLE subgroup showed a weaker survival separation.

Lung squamous cell carcinoma (LUSC)↗

PubMed2006

Development and validation of a prognostic model to predict recovery following intracerebral hemorrhage.

CONTEXT: While several models have been developed to predict mortality following intracerebral hemorrhage (ICH), the functional outcome and its predictors in surviving patients have been poorly investigated so far. OBJECTIVES: To identify predictors and validate a prognostic model for independent functional outcome in patients with acute ICH. DESIGN: An inception cohort was assessed on the National Institutes of Health Stroke Scale (NIH-SS) at admission and followed-up after 100 days. SETTING: 11 neurological departments with an acute stroke unit. PATIENTS: 207 consecutive patients who were neither comatose nor intubated at admission within 6 hours after ICH and with complete follow-up. RESULTS: After 100 days, 40 patients (19.3 %) had died, 78 (37.7%) had regained functional independence (Barthel Index > or = 95) and 89 (43%) had survived but not recovered. In these patients, age and the NIH-SS total score were identified as independent predictors for functional independence after 100 days. With the predefined cut-off value, the prognosis of 79.8% of all patients could be predicted accurately upon validation in an independent data set of 173 non-comatose patients with acute ICH. CONCLUSION: Our study provides a validated prognostic model for prediction of complete recovery following ICH which could be very useful for the design of clinical studies.

Age Factors↗

PubMed2026

GCH1, identified by a ferroptosis-related prognostic model, contributes to progression and drug resistance of esophageal cancer.

OBJECTIVE: Esophageal cancer has a poor prognosis and limited treatment options. Ferroptosis, an iron-dependent cell death pathway, is a promising therapeutic target; however, its significance in esophageal cancer remains largely unexplored. Here, we investigated the prognostic significance of ferroptosis-related genes in esophageal cancer and identified a key functional regulator that may serve as a therapeutic target. METHODS: We analyzed ferroptosis-related gene expression profiles with The Cancer Genome Atlas-Esophageal Carcinoma (TCGA-ESCA) cohort and constructed a prognostic risk model using LASSO Cox regression analysis. Among the genes in this model, GTP cyclohydrolase 1 (GCH1) was selected for functional investigation, based on its established role in antioxidant defense. Subsequently, in vitro experiments were performed to assess the effects of GCH1 knockdown on cell proliferation, migration, clonogenicity, and ferroptosis-related biochemical indicators. The role of GCH1 in antitumor immunity was evaluated through co-culture of esophageal cancer cells with activated T cells, and drug sensitivity was assessed using cytotoxicity assays. RESULTS: A prognostic model consisting of nine ferroptosis-related genes (STC2, TRIB3, HMGB3, CXCL8, GCH1, PARP10, APOE, MTIM, and GPER1) with reliable risk stratification was constructed. The prognostic model could reflect the differences in drug responses and immune cell infiltration. GCH1 knockdown suppressed esophageal cancer cell proliferation, migration, and clonogenicity. Furthermore, GCH1 knockdown increased the intracellular levels of reactive oxygen species, lipid peroxidation, and ferrous iron (Fe2+). Co-culture assays demonstrated that GCH1 knockdown in tumor cells increased the production of granzyme B and interferon-γ by CD8+ T cells. Moreover, GCH1 silencing sensitized esophageal cancer cells to both sorafenib and cisplatin. CONCLUSIONS: This study established a ferroptosis-related prognostic model for esophageal cancer and identified GCH1 as a critical regulator that contributes to esophageal cancer progression and drug resistance. These findings suggest that targeting GCH1 may be a promising strategy to improve drug sensitivity and clinical outcomes in esophageal cancer.

Esophageal cancer↗

PubMed1997

A prognostic model for the prediction of survival in cystic fibrosis.

BACKGROUND: The treatment for endstage cystic fibrosis is, where appropriate, double-lung, heart-lung or, occasionally, heart-lung-liver transplantation. Optimising the timing of transplantation depends upon an accurate prediction of survival, but while current criteria give some guidance to this, they are not based upon statistically derived prognostic models. METHODS: Data collected prospectively on 403 patients with cystic fibrosis, recruited between 1969 and 1987 (cohort A), were analysed by log rank and univariate Cox regression analysis to determine variables that accurately predict survival. The significant variables were then subject to time dependent multivariate Cox regression analysis to generate a prognostic model. The model was validated, within the study population, using split sample testing, and was subsequently validated in a further cohort of patients recruited since October 1988 (cohort B). RESULTS: One hundred and eighty eight (50.4%) of the study cohort died within the study period. Percentage predicted forced expiratory volume in one second (FEV1), percentage predicted forced vital capacity (FVC), short stature, high white cell count (WBC), and chronic liver disease (as evidenced by the presence of hepatomegaly) were negatively correlated with survival. These variables, when combined into a prognostic index, accurately predicted one year survival in the study population and in the cohort recruited since 1988. CONCLUSION: This prognostic index may prove valuable in predicting prognosis in other cohorts with cystic fibrosis and thereby improve the timing of transplantation.

Adolescent↗

PubMed2004

Long-term analysis and prospective validation of a prognostic model for patients with high-risk primary breast cancer receiving high-dose chemotherapy.

PURPOSE: We described previously a prognostic model for high-risk primary breast cancer patients receiving high-dose chemotherapy (HDC). Such model included nodal ratio (no. involved nodes:no. dissected nodes), tumor size, hormone receptors, and HER2. In the present study we intended to test this model prospectively in a second patient cohort. In addition, we analyzed the long-term overall outcome of our HDC trials. EXPERIMENTAL DESIGN: We analyzed all 264 patients enrolled since 1990 in our prospective trials for 4-9+, > or = 10+ nodes, or inflammatory disease. Patients of the second cohort (treated since 1997) had their prognostic score estimated prospectively before receiving HDC. RESULTS: Fourteen patients (5.3%) died from HDC-related complications. At median follow-up of 7.1 years, relapse-free survival and overall survival of the whole group were 69.8% and 73%, respectively. Median time to relapse was 14 months (63.5% relapses within the first 2 years, 6.7% after year 5). The model was validated in the second cohort, establishing the following pretransplant risk categories: low risk (low score, HER2-), 44% patients, 87% freedom from relapse (FFR); intermediate risk (low score, HER2+), 29% patients, 68% FFR; and high risk (high score, any HER2), 27% patients, 49% FFR. CONCLUSIONS: Few relapses are seen after year 5 of follow-up, which indicates the need for mature results of the randomized trials before their final interpretation or meta-analysis. Our prospectively validated prognostic model, if additionally confirmed in the randomized trial populations, may provide an insight into the relative benefit of HDC in different risk patient subsets.

Adult↗

PubMed2003

High-dose therapy and autologous stem cell transplantation in relapsed and refractory Hodgkin's disease: outcome based on a prognostic model.

We evaluated the results of high-dose therapy (HDT) and autologous hematopoietic stem cell transplantation (ASCT) in patients with relapsed or primary refractory Hodgkin's disease (HD), using a previously reported prognostic model based on the presence of three poor prognostic factors at the start of salvage therapy/preparative regimen: B symptoms, extranodal disease and the duration of last complete response of less than 1 year. Based on this model, the patients were divided into low-risk and high-risk groups. Between 1993 and 2001, 24 patients with HD were treated with HDT and ASCT. Eighteen of the 24 patients had 0-1 risk factors (low-risk group) and 6 patients had 2-3 risk factors (high-risk group). Using Kaplan-Meier analysis, after a median follow-up of 40.5 months, the progression-free survival (PFS) was 48%, and the overall survival (OS) was 55%. PFS in the low-risk group was 56%, and in the high-risk group 17% (p < 0.001). OS in the low-risk group was 68% and in the high-risk group it was 18% (p < 0.001). The 100-day transplant-related mortality for the entire group was 16%. Our results are comparable to those reported in previous clinical trials for patients with refractory and relapsed HD treated with HDT and ASCT. The use of a prognostic model appears useful for predicting the outcome of HDT and ASCT for HD patients, and may play an important role in choosing the appropriate therapy for these patients.

Adolescent↗

PubMed1990

The relative value of conventional staging procedures for developing prognostic models in extensive-stage small-cell lung cancer.

Published prognostic models for small-cell lung cancer (SCLC) have either combined limited- and extensive-stage patients or have not included standard anatomic staging information to assess the relative value of the knowledge of specific sites and number of sites of metastases in predicting survival in extensive-stage disease. We studied 136 extensive-stage patients in whom traditional staging procedures were performed and in whom other previously demonstrated significant pretreatment variables were determined. Using the Cox proportional hazards model, when all data were included, three variables were significant: performance status (PS) (P = .0001), number of sites of metastases (P = .0010), and age (P = .0029). A prognostic algorithm was developed using these variables, which divided the patients into three distinct groups. When the anatomic staging data were omitted, the serum albumin (P = .0313) was the only variable in addition to PS (P = .0001) and age (P = .0064) that was significant. An alternative algorithm using these three variables was nearly as predictive as the original. Therefore, in extensive-stage patients, reasonable pretreatment prognostic information can be obtained without using the number or specific sites of metastases as variables once the presence of distant metastases has been demonstrated.

Carcinoma, Small Cell↗

PubMed2005

Statistical validation of the EORTC prognostic model for malignant pleural mesothelioma based on three consecutive phase II trials.

PURPOSE: Malignant pleural mesothelioma (MPM) carries a poor prognosis due to chemoresistance. The European Organisation for Research and Treatment of Cancer (EORTC) prognostic model was reported to predict survival in MPM. Our retrospective analysis set out to test the validity of the model as a prognostic tool in patients treated in three phase II trials at St Bartholomew's Hospital (London, United Kingdom) between 1999 and 2003. PATIENTS AND METHODS: A total of 145 patients were treated in three phase II trials; vinorelbine (VIN; 70 patients), vinorelbine/oxaliplatin (VO; 26 patients), and irinotecan/cisplatin/mitomycin C (IPM; 49 patients). Two subgroups, high-risk and low-risk, were defined by EORTC prognostic score (EPS). EPS was determined by a five-parameter model incorporating age, sex, histology, probability of diagnosis, and leukocyte count. An EPS cutoff of less than 1.27 (low risk) or more than 1.27 (high risk) was used to stratify Kaplan-Meier survival curves. Each of the EPS variables exhibited either trends or significant stratification of overall survival (OS). RESULTS: Multivariate analysis confirmed leukocyte count, Eastern Cooperative Oncology Group performance status, and sarcomatous histology as independent prognostic variables. EPS stratified OS in both individual and pooled trial datasets. No association between objective tumor response and EPS classification was identified by multinomial logistic regression. EPS stratified progression-free survival for the VO and IPM cohorts, but not for VIN. CONCLUSION: This study validates the EPS system as a robust tool for stratifying small trials into low- and high-risk subgroups. EPS should facilitate patient selection and analysis in randomized clinical trials.

Adult↗

PubMed2005

Comparison of predictive accuracy of four prognostic models for nonmetastatic renal cell carcinoma after nephrectomy: a multicenter European study.

BACKGROUND: The objective of the current study was to compare, in a large multicenter study, the discriminating accuracy of four prognostic models developed to predict the survival of patients undergoing nephrectomy for nonmetastatic renal cell carcinoma (RCC). METHODS: A total of 2404 records of patients from 6 European centers were retrospectively reviewed. For each patient, prognostic scores were calculated according to four models: the Kattan model, the University of California at Los Angeles integrated staging system (UISS) model, the Yaycioglu model, and the Cindolo model. Survival curves were estimated by the Kaplan-Meier method and compared by the log-rank test. Discriminating ability was assessed by the Harrell c-index for censored data. The primary end point was overall survival (OS), and the secondary end points were cancer-specific survival (CSS) and disease recurrence-free survival (RFS). RESULTS: At last follow-up, 541 subjects had died of any causes, with a 5-year OS rate of 80%. The 5-year CSS and RFS rates were 85% and 78%, respectively. All models discriminated well (P < 0.0001). The c-indexes for OS were 0.706 for the Kattan nomogram, 0.683 for the UISS model, and 0.589 and 0.615 for the Yaycioglu and Cindolo models, respectively. The Kattan nomogram was found to improve discrimination substantially in the UISS intermediate-risk patients. CONCLUSIONS: The current study appears to better define the general applicability of prognostic models for predicting survival in patients with nonmetastatic RCC treated with nephrectomy. The results suggest that postoperative models discriminate substantially better than preoperative ones. The Kattan model was consistently found to be the most accurate, although the UISS model was only slightly less well performing. The Kattan model can be useful in the UISS intermediate-risk patients.

Adolescent↗

PubMed2006

Results of intensive chemotherapy in 998 patients age 65 years or older with acute myeloid leukemia or high-risk myelodysplastic syndrome: predictive prognostic models for outcome.

BACKGROUND: Elderly patients (age > or = 65 years) with acute myeloid leukemia (AML) generally have a poor prognosis. AML-type therapy results are often derived from studies in younger patients and may not apply to elderly AML. Many investigators and oncologists advocate, at times, only supportive care or frontline single agents, Phase I-II studies, low-intensity regimens, or 'targeted' therapies. However, baseline expectations for outcomes of elderly AML with 'standard' AML-type therapy are not well defined. The aim was to develop prognostic models for complete response (CR), induction (8-week) mortality, and survival rates in elderly AML, which would be used to advise oncologists and patients of expectations with standard AML type therapy, and to establish baseline therapy results against which novel strategies would be evaluated. METHODS: A total of 998 patients age > or = 65 years with AML or high-risk myelodysplastic syndrome (> 10% blasts) treated with intensive chemotherapy between 1980 and 2004 were analyzed. Univariate and multivariate analyses of prognostic factors associated with CR, induction (8-week) mortality, and survival used standard methods. RESULTS: The overall CR rate was 45% and induction mortality 29%. Multivariate analysis of prognostic factors identified consistent independent poor prognostic factors for CR, 8-week mortality, and survival. These included age > or = 75 years, unfavorable karyotypes (often complex), poor performance (3-4 ECOG [Eastern Cooperative Oncology Group]), longer duration of antecedent hematologic disorder, treatment outside the laminar airflow room, and abnormal organ functions. Patients could be divided into: 1) a favorable group (about 20% of patients) with expected CR rates above 60%, induction mortality rates of 10%, and 1-year survival rates above 50%; 2) an intermediate group (about 50-55% of patients) with expected CR rates of 50%, induction mortality rates of 30%, and 1-year survival rates of 30%; and 3) an unfavorable risk group (about 25-30% of patients) with expected CR rates of less than 20%, induction mortality rates above 50%, and 1-year survival rates of less than 10%. CONCLUSIONS: Prognostic models, based on standard readily available baseline characteristics, were developed for elderly patients with AML, which may assist in therapeutic and investigational decisions. These predictive models, based on a retrospective analysis, will require validation in independent study groups.

Age Factors↗

PubMedDate not supplied

[A prognostic model of a cholera epidemic].

A new model for the prognostication of cholera epidemic on the territory of a large city is proposed. This model reflects the characteristic feature of contacting infection by sensitive individuals due to the preservation of Vibrio cholerae in their water habitat. The mathematical model of the epidemic quantitatively reflects the processes of the spread of infection by kinetic equations describing the interaction of the streams of infected persons, the causative agents and susceptible persons. The functions and parameters of the model are linked with the distribution of individuals according to the duration of the incubation period and infectious process, as well as the period of asymptomatic carrier state. The computer realization of the model by means of IBM PC/AT made it possible to study the cholera epidemic which took place in Mexico in 1833. The verified model of the cholera epidemic was used for the prognostication of the possible spread of this infection in Guadalajara, taking into account changes in the epidemiological situation and the size of the population, as well as improvements in sanitary and hygienic conditions, in the city.

Cholera↗

PubMed2025

Liver cancer-specific prognostic model developed using endoplasmic reticulum stress-related LncRNAs and LINC01011 as a potential therapeutic target.

Liver cancer is a serious malignancy worldwide, and long noncoding RNAs (lncRNAs) have been implicated in its prognosis.It remains unclear how lncRNAs related to endoplasmic reticulum stress (ERS) influence liver cancer prognosis. Here, we analyzed RNA and clinical data from the Cancer Genome Atlas and sourced ERS-related genes from the Molecular Signatures Database. Co-expression analysis identified ERS-related lncRNAs, and Cox regression analysis as well as least absolute shrinkage and selection operator regression highlighted three lncRNAs for a prognostic model. Based on median risk scores, we classified patients into two risk groups. The high-risk group displayed poor prognosis, and this finding was validated in the test set. According to consistency clustering, the patients were assigned to two clusters, and tumor microenvironment scores were computed. Patients with a high mutation burden had worse outcomes. Furthermore, immune infiltration analysis indicated more immune cells and mutations in checkpoint molecules among high-risk individuals. Drug sensitivity varied between the risk groups. LINC01011 was selected for functional assays. Colony formation assay and CCK-8 assay revealed that silencing LINC01011 suppressed liver cancer cell proliferation. Transwell and scratch assays indicated that silencing LINC01011 inhibited liver cancer cell migration. Western blotting assay revealed that inhibiting LINC01011 induced apoptosis and simultaneously inhibited epithelial-mesenchymal transition. These findings confirm the validity of the prognostic model and indicate that LINC01011 could serve as a potential research target.

Humans↗

PubMed1997

The role of prognostic models in the timing of liver transplantation. Application in cholestatic liver diseases.

Prognostic models have been developed for patients with primary biliary cirrhosis and primary sclerosing cholangitis to predict survival without transplantation. In patients undergoing liver transplantation, these models have been used in assessing postoperative mortality and morbidity. Recent data suggest that preoperative recipient physiology, such as impaired functional status or renal insufficiency, is the most important determinant of transplant outcome. Survival, quality of life, morbidities and resource use are the key variables to be considered in the timing of transplantation.

Cholangitis, Sclerosing↗

PubMed2006

Performance and customization of 4 prognostic models for postoperative onset of nausea and vomiting in ear, nose, and throat surgery.

OBJECTIVE: To evaluate the performance of 4 published prognostic models for postoperative onset of nausea and vomiting (PONV) by means of discrimination and calibration and the possible impact of customization on these models. DESIGN: Prospective, observational study. SETTING: Tertiary care university hospital. PATIENTS: 748 adult patients (>18 years old) enrolled in this study. Severe obesity (weight > 150 kg or body mass index > 40 kg/m) was an exclusion criterion. INTERVENTIONS: All perioperative data were recorded with an anesthesia information management system. A standardized patient interview was performed on the postoperative morning and afternoon. MEASUREMENTS: Individual PONV risk was calculated using 4 original regression equations by Koivuranta et al, Apfel et al, Sinclair et al, and Junger et al Discrimination was assessed using receiver operating characteristic (ROC) curves. Calibration was tested using Hosmer-Lemeshow goodness-of-fit statistics. New predictive equations for the 4 models were derived by means of logistic regression (customization). The prognostic performance of the customized models was validated using the "leaving-one-out" technique. MAIN RESULTS: Postoperative onset of nausea and vomiting was observed in 11.2% of the specialized patient population. Discrimination could be demonstrated as shown by areas under the receiver operating characteristic curve of 0.62 for the Koivuranta et al model, 0.63 for the Apfel et al model, 0.70 for the Sinclair et al model, and 0.70 for the Junger et al model. Calibration was poor for all 4 original models, indicated by a P value lower than 0.01 in the C and H statistics. Customization improved the accuracy of the prediction for all 4 models. However, the simplified risk scores of the Koivuranta et al model and the Apfel et al model did not show the same efficiency as those of the Sinclair et al model and the Junger et al model. This is possibly a result of having relatively few patients at high risk for PONV in combination with an information loss caused by too few dichotomous variables in the simplified scores. CONCLUSIONS: The original models were not well validated in our study. An antiemetic therapy based on the results of these scores seems therefore unsatisfactory. Customization improved the accuracy of the prediction in our specialized patient population, more so for the Sinclair et al model and the Junger et al model than for the Koivuranta et al model and the Apfel et al model.

Adolescent↗

PubMedDate not supplied

[Prognostic model of drug abuse and HIV infection morbidity among youth].

The description of prognostication model the distribution process of a narcotism (the heroine) among youth of large city is given. The model is developed with the purpose of study of a consequence of a narcotism among the teenagers and youth, which use a intravenous drugs user and have high risk of infection by a HIV-infection. The results of settlement researches heroine epidemic process in large city with the population about 1 million on retrospective per 10 years are submitted. The forecast of number of drug users on prospect per 5 years is made. It allows to estimate long-term consequences of a narcotism, as "has sunk down" for powerful epidemic AIDS in city in nearest 10 years.

Adolescent↗

PubMed2003

A new prognostic model for testicular germ cell tumours.

In univariate analyses of patients with metastatic testicular germ cell tumours (TGCT), both the International Germ Cell Consensus Classification (IGCCC) and serum lactate dehydrogenase (S-LD) isoenzyme 1 catalytic concentration (S-LD-1) significantly predicted survival. In complementary analyses of 81 patients with metastatic TGCT, S-LD and S-LD-1 classified the prognosis differently for 23 patients. In multivariate Cox hazard analyses of risk factors, only IGCCC and S-LD-1 predicted the prognosis (p=0.036, and p=0.0007, respectively). A new prognostic model based on prognostic information from main histology, IGCCC, and S-LD-1 changed the prognostic prediction by IGCCC for 19 patients (24%). Judged by to the area under the curve for receiver operation characteristics curves, the new model predicted five-years survival for the patients better than IGCCC and a modified version of the third edition of the TNM classification (p=0.025, and p=0.01, respectively). However, new studies should validate the new model before it is recommended as a general classification system of patients with metastatic TGCT.

Biomarkers, Tumor↗

PubMed2003

Prognostic model for predicting survival in men with hormone-refractory metastatic prostate cancer.

PURPOSE: To develop and validate a model that can be used to predict the overall survival probability among metastatic hormone-refractory prostate cancer patients (HRPC). PATIENTS AND METHODS: Data from six Cancer and Leukemia Group B protocols that enrolled 1,101 patients with metastatic hormone-refractory adenocarcinoma of the prostate during the study period from 1991 to 2001 were pooled. The proportional hazards model was used to develop a multivariable model on the basis of pretreatment factors and to construct a prognostic model. The area under the receiver operating characteristic curve (ROC) was calculated as a measure of predictive discrimination. Calibration of the model predictions was assessed by comparing the predicted probability with the actual survival probability. An independent data set was used to validate the fitted model. RESULTS: The final model included the following factors: lactate dehydrogenase, prostate-specific antigen, alkaline phosphatase, Gleason sum, Eastern Cooperative Oncology Group performance status, hemoglobin, and the presence of visceral disease. The area under the ROC curve was 0.68. Patients were classified into one of four risk groups. We observed a good agreement between the observed and predicted survival probabilities for the four risk groups. The observed median survival durations were 7.5 (95% confidence interval [CI], 6.2 to 10.9), 13.4 (95% CI, 9.7 to 26.3), 18.9 (95% CI, 16.2 to 26.3), and 27.2 (95% CI, 21.9 to 42.8) months for the first, second, third, and fourth risk groups, respectively. The corresponding median predicted survival times were 8.8, 13.4, 17.4, and 22.80 for the four risk groups. CONCLUSION: This model could be used to predict individual survival probabilities and to stratify metastatic HRPC patients in randomized phase III trials.

Adenocarcinoma↗

PubMed1995

The SUPPORT prognostic model. Objective estimates of survival for seriously ill hospitalized adults. Study to understand prognoses and preferences for outcomes and risks of treatments.

OBJECTIVE: To develop and validate a prognostic model that estimates survival over a 180-day period for seriously ill hospitalized adults (phase I of SUPPORT [Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments]) and to compare this model's predictions with those of an existing prognostic system and with physicians' independent estimates (SUPPORT phase II). DESIGN: Prospective cohort study. SETTING: 5 tertiary care academic centers in the United States. PARTICIPANTS: 4301 hospitalized adults were selected for phase I according to diagnosis and severity of illness; 4028 patients were evaluated from phase II. MEASUREMENTS: A survival model was developed using the following predictor variables: diagnosis, age, number of days in the hospital before study entry, presence of cancer, neurologic function, and 11 physiologic measures recorded on day 3 after study entry. Physicians were interviewed on day 3. Patients were followed for survival for 180 days after study entry. RESULTS: The area under the receiver-operating characteristics (ROC) curve for prediction of surviving 180 days was 0.79 in phase I, 0.78 in the phase II independent validation, and 0.78 when the acute physiology score from the APACHE (Acute Physiology, Age, Chronic Health Evaluation) III prognostic scoring system was substituted for the SUPPORT physiology score. For phase II patients, the SUPPORT model had equal discrimination and slightly improved calibration compared with physician's estimates. Combining the SUPPORT model with physician's estimates improved both predictive accuracy (ROC curve area = 0.82) and the ability to identify patients with high probabilities of survival or death. CONCLUSIONS: A limited amount of readily available clinical information can provide a foundation for long-term survival estimates that are as accurate as physicians' estimates. The best survival estimates combine an objective prognosis with a physician's clinical estimate.

APACHE↗