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At least 37 records · Page 2Linked to original sources
PubMed2003

External validation of the SAPS II, APACHE II and APACHE III prognostic models in South England: a multicentre study.

OBJECTIVE: External validation of three prognostic models in adult intensive care patients in South England. DESIGN. Prospective cohort study. SETTING: Seventeen intensive care units (ICU) in the South West Thames Region in South England. PATIENTS AND PARTICIPANTS: Data of 16646 patients were analysed. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: We compared directly the predictive accuracy of three prognostic models (SAPS II, APACHE II and III), using formal tests of calibration and discrimination. The external validation showed a similar pattern for all three models tested: good discrimination, but imperfect calibration. The areas under the receiver operating characteristics (ROC) curves, used to test discrimination, were 0.835 and 0.867 for APACHE II and III, and 0.852 for the SAPS II model. Model calibration was assessed by Lemeshow-Hosmer C-statistics and was Chi(2 )=232.1 for APACHE II, Chi(2 )=443.3 for APACHE III and Chi(2 )=287.5 for SAPS II. CONCLUSIONS: Disparity in case mix, a higher prevalence of outcome events and important unmeasured patient mix factors are possible sources for the decay of the models' predictive accuracy in our population. The lack of generalisability of standard prognostic models requires their validation and re-calibration before they can be applied with confidence to new populations. Customisation of existing models may become an important strategy to obtain authentic information on disease severity, which is a prerequisite for reliably measuring and comparing the quality and cost of intensive care.

APACHE↗
PubMed2006

Validation of the SAPS 3 admission prognostic model in patients with cancer in need of intensive care.

OBJECTIVES: To validate the SAPS 3 admission prognostic model in patients with cancer admitted to the intensive care unit (ICU). DESIGN: Cohort study. SETTING: Ten-bed medical-surgical oncologic ICU. PATIENTS AND PARTICIPANTS: Nine hundred and fifty-two consecutive patients admitted over a 3-year period. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: Data were prospectively collected at admission of ICU. SAPS II and SAPS 3 scores with respective estimated mortality rates were calculated. Discrimination was assessed by area under receiver operating characteristic (AUROC) curves and calibration by Hosmer-Lemeshow goodness-of-fit test. The mean age was 58.3+/-23.1 years; there were 471 (49%) scheduled surgical, 348 (37%) medical and 133 (14%) emergency surgical patients. ICU and hospital mortality rates were 24.6% and 33.5%, respectively. The mean SAPS 3 and SAPS II scores were 52.3+/-18.5 points and 35.3+/-20.7 points, respectively. All prognostic models showed excellent discrimination (AUROC>or=0.8). The calibration of SAPS II was poor (p<0.001). However, the calibration of standard SAPS 3 and its customized equation for Central and South American (CSA) countries were appropriate (p>0.05). SAPS II and standard SAPS 3 prognostic models tended somewhat to underestimate the observed mortality (SMR>1). However, when the customized equation was used, the estimated mortality was closer to the observed mortality [SMR=0.95 (95% CI=0.84-1.07)]. Similar results were observed when scheduled surgical patients were excluded. CONCLUSIONS: The SAPS 3 admission prognostic model at ICU admission, in particular its customized equation for CSA, was accurate in our cohort of critically ill patients with cancer.

Female↗
PubMed1994

Intermediate-grade lymphomas treated with cyclophosphamide-doxorubicin- vincristine-prednisone-bleomycin alternated with cyclophosphamide-methotrexate-etoposide-dexamethasone. Application of prognostic models to data analysis.

BACKGROUND: Numerous treatment strategies have been tried with the aim of improving results for patients with intermediate-grade lymphomas (IGL) over those achieved with cyclophosphamide, doxorubicin, vincristine, prednisone, and bleomycin (CHOP-Bleo), and numerous prognostic models have been developed to identify and separate risk groups. This study reports on a new protocol for Ann Arbor Stages II-IV IGL that consists of CHOP-Bleo alternated with a new regimen of cyclophosphamide, methotrexate, etoposide, and dexamethasone (CMED) and radiation therapy and demonstrates the usefulness of prognostic models for identifying risk groups and comparing treatment programs. METHODS: One hundred seventy patients with Ann Arbor Stages II-IV IGL were treated with alternating cycles of CHOP-Bleo and CMED for a total of 12 cycles. Involved field radiation therapy was interspersed with courses of chemotherapy for patients with Stage II and Stage III disease. Results were analyzed and compared with those of the authors' previous study of CHOP-Bleo and radiation therapy using the Ann Arbor staging system, their earlier prognostic model, and the recently published International Index. RESULTS: A complete remission occurred in 78% of the patients. The overall 5-year survival rate was 67%. Survival was better for patients with Ann Arbor Stage II disease (80%) than for those with Stage III or Stage IV (67% and 58%, respectively). High tumor burden, above-normal levels of serum lactic dehydrogenase, serum beta 2-microglobulin, and Ann Arbor Stage IV disease were adverse factors. The International Index and the authors' earlier prognostic model separated four prognostic groups. CHOP-Bleo/CMED was generally well tolerated. Neutropenic fever was the major complication that occurred in 25 patients during treatment. Six of these patients died of sepsis. CONCLUSIONS: This study demonstrated that CHOP-Bleo/CMED is a well-tolerated regimen that produced better results than those reported for a former study that used CHOP-Bleo alone. Further, results for CHOP-Bleo/CMED compared favorably with those of other second- and third-generation regimens. The study also validated the usefulness of prognostic models and, in particular, the new International Index for identifying risk groups.

Adolescent↗
PubMed2005

Prognostic model of event-free survival for patients with androgen-independent prostate carcinoma.

BACKGROUND: The current study was conducted to develop a prognostic model of event-free survival (EFS) in men with androgen-independent prostate carcinoma (AIPC). METHODS: Data from 160 patients diagnosed with AIPC between 1989-2002 were reviewed. No patient had received cytotoxic chemotherapy. A univariate Cox proportional hazards model identified significant predictors of EFS. Recursive partitioning analysis divided these significant variables into prognostic risk groups. The final prognostic model was tested with a Cox proportional hazards model. RESULTS: The final prognostic risk model included the presence of metastatic disease at the time of androgen-independent disease progression (P = 0.040), time to prostate-specific antigen (PSA) recurrence (P = 0.043), and PSA doubling time (P < 0.01). Three highly independent risk groups were identified. The observed median EFSs were 6.1 months (95% confidence interval [95= CI], 3.4-8.8 months), 33.6 months (95= CI, 25.3-41.9 months), and 96.1 months (95= CI, 57.9-134.3 months) for the low-risk, intermediate-risk, and high-risk groups, respectively. Each risk group was found to be independently predictive of EFS (P < 0.01). Patients who died of prostate carcinoma experienced significantly more clinical events than those who died of other causes (P < 0.01). CONCLUSIONS: The prognostic model in the current study stratified patients into three highly significant and independent risk groups for EFS. A detailed PSA history and knowledge of metastatic disease are sufficient to risk-stratify patients with AIPC. One very unique aspect of this model was that it was developed from a patient cohort that never received chemotherapy.

Aged↗
PubMed1998

External validation of prognostic models for ongoing pregnancy after in-vitro fertilization.

This study aimed to validate prognostic models for predicting ongoing pregnancy after the first and second in-vitro fertilization cycles. Models were developed using data from the University Hospital, Nijmegen, 1991-1994 and tested using more recent data from the same centre and data from two other centres. Although the variables included in the models seemed plausible, the predictions of the models were unsatisfactory. The models did not discriminate between women who had achieved pregnancy and women who did not achieve pregnancy; neither could they indicate which women had a (very) low probability of ongoing pregnancy. Taking into account the success rate of a specific clinic or the success rate during a specific period did not show any advantage. The predictions were even inaccurate in the same hospital during another period. It is obvious that these prognostic models should not be used. This study shows the importance of validating prognostic models before their implementation in clinical practice.

Adult↗
PubMed2005

A prognostic model for prolonged event-free survival after autologous or allogeneic blood or marrow transplantation for relapsed and refractory Hodgkin's disease.

There are several prognostic models for Hodgkin's disease (HD) patients, but none evaluating patient characteristics at time of blood and marrow transplantation (BMT). We developed a prognostic model for event-free survival (EFS) post-BMT based on HD patient characteristics measured at the time of autologous (auto) or allogeneic (allo) BMT. Between 1/1991 and 12/2001, 64 relapsed or refractory HD patients received an auto (n=46) or allo (n=18) BMT. A multivariate prognostic model was developed measuring time to relapse, progression or death. Median follow-up was 51.7 months; median EFS for auto and allo BMT was 36 and 3 months, respectively (P=0.001). Significant multivariate predictors of shorter EFS were chemotherapy-resistant disease, KPS <90 and > or =3 chemotherapy regimens pre-BMT. Patients with two to three adverse factors had significantly shorter EFS at 2 years (58 vs 11% in auto; 38 vs 0% in allo BMT patients). Despite a selection bias favoring auto BMT, the model was valid in both auto and allo BMT groups. We were able to differentiate patients at high vs low risk for adverse outcomes post-BMT. This prognostic model may prove useful in predicting patient outcomes and identifying high-risk patients for novel treatment strategies. Validation of this model in a larger cohort of patients is warranted.

Adult↗
PubMed2000

[Management of breech delivery in term pregnancy: own diagnostic and prognostic model].

Using own diagnostic and prognostic model, 1157 pregnant women with breech presentation in term were analysed. In 1008 cases (87.1%) they delivered according to prognosis established formerly. Manual support in delivery was required in 748 cases (64.6%). Elective caesarean section was performed in 260 women (22.5%). In 149 cases (12.9%) immediate caesarean section appeared, because of additional reasons, despite normal delivery prognosis.

Breech Presentation↗
PubMed2026

Development and internal validation of a six-gene prognostic model based on galactose metabolism for overall survival in lung adenocarcinoma.

BACKGROUND: Lung cancer remains a leading cause of cancer incidence and mortality globally. Metabolic reprogramming promotes tumor progression and shapes an immunosuppressive tumor microenvironment. Galactose metabolism is involved in multiple malignancies, but its prognostic value in lung adenocarcinoma (LUAD) remains unclear. This study aimed to develop and internally validate a galactose metabolism-related multigene prognostic model for LUAD. METHODS: A retrospective prognostic model development and internal validation study was performed using RNA sequencing (RNA-seq) and clinical data from 585 LUAD patients in The Cancer Genome Atlas (TCGA). Differential expression, functional enrichment, univariate and multivariate Cox regression were applied to construct a prognostic gene signature. Internal validation was performed using bootstrap resampling. Model performance was evaluated by time-dependent receiver operating characteristic (ROC), C-index, calibration, and Kaplan-Meier analysis. Associations between the model and immune infiltration, immunotherapy responsiveness, and tumor stemness were also analyzed. RESULTS: A six-gene prognostic model (GALT, GANC, PGM1, GALM, B4GALT1, PGM2) was developed. The model showed good discrimination with 1-, 3-, and 5-year area under the curve (AUC) values of 0.719, 0.693, and 0.684, respectively. The low-risk group exhibited significantly longer survival, increased antitumor immune infiltration (CD8+ T cells, M1 macrophages, activated CD4+ memory T cells), higher expression of T cell proliferation-related genes, lower immune checkpoint expression, better predicted immunotherapy response, and lower tumor stemness compared with the high-risk group. CONCLUSIONS: We developed and internally validated a six-gene prognostic model for LUAD based on galactose metabolism. The model shows moderate prognostic performance and is associated with antitumor immunity and tumor stemness. It may be used for prognostic risk stratification and to guide personalized immunotherapy in LUAD.

Galactose metabolism↗
PubMed2006

Prognostic factor analysis and proposed prognostic model for conventional treatment of high-grade primary gastric lymphoma.

OBJECTIVES: We conducted a clinical risk factors analysis to define a prognostic model for high-grade primary gastric lymphoma (HG-PGL). METHODS AND RESULTS: The median event-free survival and overall survival of 214 HG-PGL patients were 54 and 104.5 months, respectively, after a median follow-up duration of 60 months. According to the prognostic factor analysis, survival, advanced age, male gender, higher LDH levels and the presence of ascites were identified as independent prognostic factors for HG-PGL. We identified four groups at different risk: group 1, no adverse effect; group 2, one factor; group 3, two factors; group 4, three or four factors. The new prognostic model showed excellent prognostic capacity to differentiate subgroups according to their risk stratification. CONCLUSIONS: The proposed new prognostic model for HG-PGL demonstrated a balanced distribution of patients into four groups with good prognostic capacity.

Adult↗
PubMed2006

Developing a prognostic model for 90-day mortality after liver transplantation based on pretransplant recipient factors.

BACKGROUND: Current statistical prognostic models for mortality after liver transplantation do not have good discriminatory ability. Furthermore, the methodology used to develop these models is often flawed. The objective of this paper is to develop a prognostic model for 90-day mortality after liver transplantation based on pretransplant recipient factors, employing a rigorous model development method. METHODS: We used data on 4,829 patient that were prospectively collected for the UK & Ireland Liver Transplant Audit. Switching regression was employed to impute missing values combined with a bootstrapping approach for variable selection. RESULTS: In all, 452 patients (9.4%) died within 90 days of their transplantation. The final prognostic model was well calibrated and discriminated moderately well between patients who did and who did not die (c-statistic 0.65, 95% CI [0.63, 0.68]). Although discrimination was not excellent overall, the results showed that those patients with a "low" chance of dying within 90 days of their transplant and those with a "high" chance of dying could be differentiated from patients with a "intermediate" chance. CONCLUSIONS: Our model can provide transplant candidates with predictions of their early posttransplantation prospects before any donor information is known, which is essential information for patients with end-stage liver disease for whom liver transplantation is a treatment option.

Adult↗
PubMed2003

Simple clinical prognostic model for hepatocellular carcinoma in developing countries and its validation.

PURPOSE: More than 80% of hepatocellular carcinomas (HCCs) worldwide occur in developing countries, especially in Asia. It often presents at an advanced stage beyond treatment. In this circumstance, a simple prognostic model is useful. Previous prognostic models require radiologic and laboratory investigations that are not readily available in developing countries. Our aim is to formulate and then validate a simple clinical prognostic model for HCC in an Asian population using only clinical parameters and with serum alpha-fetoprotein (AFP) as the sole laboratory test. PATIENTS AND METHODS: Cox regression modeling was performed on several clinical parameters and serum AFP level in 397 patients with HCC who received only supportive care in Singapore. A later group of 324 HCC patients from an Asia-Pacific-wide randomized trial was then used to validate the model. RESULTS: Ascites, physical performance status, and serum AFP were independently predictive of survival. Cox analysis yielded a simple score based on these three variables that categorizes patients into low-, medium-, and high-risk groups with 6-month survivals of 43%, 21%, and 5%, respectively. The prospective validation data provided corresponding estimates of 33%, 15%, and 3% and give confirmation of the utility of the simple model. CONCLUSION: We have formulated and prospectively validated a simple prognostic score for untreated HCC that only requires a clinical evaluation for ascites and physical performance status and measurement of serum AFP. This simple model is particularly apt for developing country circumstances and can also be used to select patients for treatment trials.

Adult↗
PubMed2005

Systematic review and validation of prognostic models in liver transplantation.

A model that can accurately predict post-liver transplant mortality would be useful for clinical decision making, would help to provide patients with prognostic information, and would facilitate fair comparisons of surgical performance between transplant units. A systematic review of the literature was carried out to assess the quality of the studies that developed and validated prognostic models for mortality after liver transplantation and to validate existing models in a large data set of patients transplanted in the United Kingdom (UK) and Ireland between March 1994 and September 2003. Five prognostic model papers were identified. The quality of the development and validation of all prognostic models was suboptimal according to an explicit assessment tool of the internal, external, and statistical validity, model evaluation, and practicality. The discriminatory ability of the identified models in the UK and Ireland data set was poor (area under the receiver operating characteristic curve always smaller than 0.7 for adult populations). Due to the poor quality of the reporting, the methodology used for the development of the model could not always be determined. In conclusion, these findings demonstrate that currently available prognostic models of mortality after liver transplantation can have only a limited role in clinical practice, audit, and research.

Humans↗
PubMed2006

Tumor-marker analysis and verification of prognostic models in patients with cancer of unknown primary, receiving platinum-based combination chemotherapy.

OBJECTIVES: To evaluate the usefulness of tumor-marker measurements and to identify prognostic factors in patients with cancer of unknown primary (CUP), receiving platinum-based combination chemotherapy and to verify the adjustment of previously reported prognostic models in this population. METHODS: We conducted univariate and multivariate analyses in consecutive patients with CUP receiving platinum-based combination chemotherapy. Previously reported prognostic models were then validated in this population. RESULTS: A total of 93 patients were analyzed and the response rate to platinum-based chemotherapeutic regimens among the 93 patients was 39.8%. The median time to progression and overall survival period were 4.1 and 12.4 months, respectively. The ST-439 level was significantly higher in patients with histologically confirmed adenocarcinoma than in patients with poorly differentiated adenocarcinoma or poorly differentiated carcinoma. A multivariate analysis indicated that performance status, the number of involved organs, and the serum lactate dehydrogenase level were the prognostic factors of the outcome. Both the previously reported prognostic models for predicting the duration of survival in this population were shown to be valid. CONCLUSION: Tumor-marker measurements are not helpful in the management of patients with CUP. Previously reported prognostic models may be useful for selecting indication for chemotherapy or for stratifying the patients in clinical trial.

Adult↗
PubMed2000

Using prognostic models in clinical infertility.

The chance that a couple who have tried to conceive for 12 months will succeed without assisted conception treatment is still higher than the chance that the same couple will benefit from treatment. In this context, it is important to assess the chance that a treatment-independent or 'spontaneous' pregnancy will occur in a couple whose wish for a child is unfulfilled. Prognostic models can be useful in this assessment. In recent years, prognostic models have been published both for the occurrence of 'spontaneous' pregnancy and for pregnancy after in vitro fertilization. This article discusses the theoretical aspects of prognostic modelling and assesses whether the current prognostic models are good enough to justify their use in clinical practice. The performance of existing models for the prediction of spontaneous conception was found to be acceptable on internal as well as on external validation. However, the performance of the existing models predicting IVF outcome was found to be disappointing on the few occasions on which such external validation has been performed.

Journal Article↗
PubMed2005

Elevated neutrophil and monocyte counts in peripheral blood are associated with poor survival in patients with metastatic melanoma: a prognostic model.

We aimed to create a prognostic model in metastatic melanoma based on independent prognostic factors in 321 patients receiving interleukin-2 (IL-2)-based immunotherapy with a median follow-up time for patients currently alive of 52 months (range 15-189 months). The patients were treated as part of several phase II protocols and the majority received treatment with intermediate dose subcutaneous IL-2 and interferon-alpha. Neutrophil and monocyte counts, lactate dehydrogenase (LDH), number of metastatic sites, location of metastases and performance status were all statistically significant prognostic factors in univariate analyses. Subsequently, a multivariate Cox's regression analysis identified elevated LDH (P<0.001, hazard ratio 2.8), elevated neutrophil counts (P=0.02, hazard ratio 1.4) and a performance status of 2 (P=0.008, hazard ratio 1.6) as independent prognostic factors for poor survival. An elevated monocyte count could replace an elevated neutrophil count. Patients were assigned to one of three risk groups according to the cumulative risk defined as the sum of simplified risk scores of the three independent prognostic factors. Low-, intermediate- and high-risk patients achieved a median survival of 12.6 months (95% confidence interval (CI), 11.4-13.8), 6.0 months (95% CI, 4.8-7.2) and 3.4 months (95% CI, 1.2-5.6), respectively. The low-risk group encompassed the majority of long-term survivors, whereas the patients in the high-risk group with a very poor prognosis should probably not be offered IL-2-based immunotherapy.

Adult↗
PubMed2006

Some prognostic models for traumatic brain injury were not valid.

OBJECTIVE: Various prognostic models have been developed to predict outcome after traumatic brain injury (TBI). We aimed to determine the validity of six models that used baseline clinical and computed tomographic characteristics to predict mortality or unfavorable outcome at 6 months or later after severe or moderate TBI. STUDY DESIGN AND SETTING: The validity was studied in two selected series of TBI patients enrolled in clinical trials (Tirilazad trials; n = 2,269; International Selfotel Trial; n = 409) and in two unselected series of patients consecutively admitted to participating centers (European Brain Injury Consortium [EBIC] survey; n = 796; Traumatic Coma Data Bank; n = 746). Validity was indicated by discriminative ability (AUC) and calibration (Hosmer-Lemeshow goodness-of-fit test). RESULTS: The models varied in number of predictors (four to seven) and in development technique (two prediction trees and four logistic regression models). Discriminative ability varied widely (AUC: .61-.89), but calibration was poor for most models. Better discrimination was observed for logistic regression models compared with trees, and for models including more predictors. Further, discrimination was better when tested on unselected series that contained more heterogeneous populations. CONCLUSION: Our findings emphasize the need for external validation of prognostic models. The satisfactory discrimination indicates that logistic regression models, developed on large samples, can be used for classifying TBI patients according to prognostic risk.

Area Under Curve↗
PubMed2006

Systematic review of prognostic models in traumatic brain injury.

BACKGROUND: Traumatic brain injury (TBI) is a leading cause of death and disability world-wide. The ability to accurately predict patient outcome after TBI has an important role in clinical practice and research. Prognostic models are statistical models that combine two or more items of patient data to predict clinical outcome. They may improve predictions in TBI patients. Multiple prognostic models for TBI have accumulated for decades but none of them is widely used in clinical practice. The objective of this systematic review is to critically assess existing prognostic models for TBI METHODS: Studies that combine at least two variables to predict any outcome in patients with TBI were searched in PUBMED and EMBASE. Two reviewers independently examined titles, abstracts and assessed whether each met the pre-defined inclusion criteria. RESULTS: A total of 53 reports including 102 models were identified. Almost half (47%) were derived from adult patients. Three quarters of the models included less than 500 patients. Most of the models (93%) were from high income countries populations. Logistic regression was the most common analytical strategy to derived models (47%). In relation to the quality of the derivation models (n:66), only 15% reported less than 10% pf loss to follow-up, 68% did not justify the rationale to include the predictors, 11% conducted an external validation and only 19% of the logistic models presented the results in a clinically user-friendly way CONCLUSION: Prognostic models are frequently published but they are developed from small samples of patients, their methodological quality is poor and they are rarely validated on external populations. Furthermore, they are not clinically practical as they are not presented to physicians in a user-friendly way. Finally because only a few are developed using populations from low and middle income countries, where most of trauma occurs, the generalizability to these setting is limited.

Brain Injuries↗
PubMed2006

Hepatic resection for noncolorectal nonendocrine liver metastases: analysis of 1,452 patients and development of a prognostic model.

OBJECTIVE: To determine the utility of hepatic resection (HR) in the treatment of patients with noncolorectal nonendocrine liver metastases (NCNELM). SUMMARY BACKGROUND DATA: The place of HR in the treatment of NCNELM remains controversial, primarily due to the limitations of previously published reports and the heterogeneity of primary tumor sites and histologies. METHODS: A multivariate risk model was developed by analyzing prognostic factors and long-term outcomes in 1452 patients with NCNELM treated with HR at 41 centers from 1983 to 2004. RESULTS: Hepatic metastases were solitary in 56% and unilateral in 71% (mean diameter, 50.5 mm). Extrahepatic metastases were present in 22%. The most common primary sites were breast (32%), gastrointestinal (16%), and urologic (14%). The most common histologies were adenocarcinoma (60%), GIST/sarcoma (13.5%), and melanoma (13%). R0 resection was achieved in 83% of patients with a 60-day mortality rate of 2.3% and a major complication rate of 21.5%. Tumor recurred in 67% of patients (liver, 24%; extrahepatic, 18%; both, 25%). Overall and disease-free survivals at 5 years were 36% and 21% and at 10 years were 23% and 15%, respectively. In multivariate analysis, factors associated with poor prognosis were patient age >60 years, nonbreast origin, melanoma or squamous histology, disease-free interval <12 months, extrahepatic metastases, R2 resection, and major hepatectomy (all P < or = 0.02). A prognostic model based on these factors effectively stratified patients into low-risk (0-3 points, 46% 5-year survival), mid-risk (4-6 points, 33% 5-year survival), and high-risk (>6 points, <10% 5-year survival) groups (P = 0.0001). DISCUSSION: HR for NCNELM is safe and effective, with outcomes mainly dependent on primary tumor site and histology. For individual patients, a statistical model based on key prognostic factors could validate the indication for hepatic resection by predicting long-term survivals.

Adolescent↗