[The mathematical models of prognosticating intravenous infusion extravasation].
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Case-Control Studies↗
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Results for “Prognostic model”
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Novel environmental contaminant 6PPD-quinone promotes malignant phenotypes in colorectal cancer cells and identifies candidate response-associated genes.
6PPD-quinone (6PPDQ), an oxidative transformation product of the widely used tire antioxidant 6PPD, is a ubiquitous environmental contaminant with bioaccumulation potential and widespread human exposure. Recent epidemiological evidence indicates a positive association between urinary 6PPDQ levels and colorectal cancer (CRC) risk; however, its biological effects on CRC-related phenotypes and associated molecular responses remain unclear. We integrated bioinformatics analysis, prognostic modeling, molecular docking and dynamics simulations, and in vitro experiments to investigate cellular and molecular responses to 6PPDQ in CRC models. Predicted 6PPDQ targets were intersected with CRC prognosis-related genes from The Cancer Genome Atlas, followed by functional enrichment and LASSO regression to construct a prognostic risk model, with 1-, 3-, and 5-year AUC values of 0.727, 0.754, and 0.778, respectively. Molecular docking and 100-ns molecular dynamics simulations suggested interactions between 6PPDQ and candidate proteins, including CPT2, SHC2, SRMS, and STK35. Functional assays showed that 6PPDQ exposure altered proliferation, wound-closure capacity, and invasion in Caco-2 and HCT116 cells across the nanomolar concentration range, with non-monotonic and cell-line-dependent responses. In contrast, NCM460 cells showed no increase in EdU incorporation at 10 or 100 nM, whereas reduced proliferation at higher concentrations was accompanied by increased LDH release. 6PPDQ also altered the expression of several prognosis-associated candidate genes. These findings identify cellular phenotypes and candidate molecular responses associated with 6PPDQ exposure under the tested in vitro conditions, but do not establish their causal roles or in vivo relevance. Further mechanistic and in vivo studies are required.
Humans↗
Characterization, outcome, and prognosis in 273 patients with primary sclerosing cholangitis: A single center study.
OBJECTIVES: Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease with varying severity and progression. This study describes the natural history of PSC patients and evaluates the prognostic significance of clinical, biochemical, and cholangiographic findings constructing a novel prognostic model. METHODS: A population of 273 German PSC patients was studied with a median follow-up time of 76 months (range 1-280 months). Survival curves were analyzed by the Kaplan-Meier method, and prognostic significance of clinical, biochemical, and cholangiographic features recorded at the time of diagnosis was evaluated by multivariate analysis using Cox proportional-hazards regression models. RESULTS: The estimated median survival from the time of diagnosis to death or time of liver transplantation was 9.6 yr. One hundred eight (39.6%) patients underwent liver transplantation. Hepatobiliary malignancies were found in 39 (14.3%) patients of the entire PSC population. Age, low albumin, persistent bilirubin elevation longer than 3 months, hepatomegaly, splenomegaly, dominant bile duct stenosis, and intra- and extrahepatic ductal changes at the time of diagnosis were found to be independent risk factors correlating with poor prognosis and were used to construct a new prognostic model. CONCLUSIONS: A persistent bilirubin elevation for longer than 3 months from the time of diagnosis could be identified as a novel marker correlating with a poor outcome. A new prognostic model was developed to predict progression of PSC, which may be useful in timing of liver transplantation.
Adolescent↗
Lipid Metabolism-related lncRNA Model Identifies AC026412.3 as a Driver of Fatty Acid β-oxidation in Hepatocellular Carcinoma.
BACKGROUND AND AIMS: Dysregulated lipid metabolism contributes to hepatocellular carcinoma (HCC) progression, but the prognostic value and mechanistic roles of lipid metabolism-related long noncoding RNAs (LRLs) remain insufficiently characterized. This study aimed to construct and validate an LRL-based prognostic model and to investigate the biological function and metabolic mechanism of AC026412.3 in HCC. METHODS: Transcriptomic and clinical data from the The Cancer Genome Atlas Liver Hepatocellular Carcinoma cohort were analyzed to identify LRLs based on their correlation with curated lipid metabolism genes. Differential expression, univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analyses were performed to construct a prognostic signature, which was evaluated using Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) analyses. Functional enrichment analyses Gene Ontology [GO], Kyoto Encyclopedia of Genes and Genomes [KEGG] and gene set enrichment analysis [GSEA], mutation profiling, tumor mutational burden, immune infiltration estimation, and consensus clustering were applied to characterize associated features. A key LRL was identified through integrated bioinformatic screening and prioritization. Its biological role was assessed by quantitative reverse transcription polymerase chain reactionq (RT-PCR), western blotting, BODIPY staining, colony formation, Transwell assays, and xenograft models. RNA sequencing followed by pathway enrichment analysis was conducted to explore underlying mechanisms. RESULTS: A three-LRL signature (AL031985.3, NRAV, and AC026412.3) stratified HCC patients into distinct risk groups with significantly different survival outcomes and demonstrated independent prognostic value. AC026412.3 was markedly upregulated in HCC and associated with poor prognosis. Functional assays demonstrated that AC026412.3 promoted proliferation, invasion, and tumor growth while reducing lipid accumulation. Mechanistically, AC026412.3 upregulated solute carrier family 22 member 5 (SLC22A5), enhanced fatty acid β-oxidation, and increased adenosine triphosphate (ATP) production, thereby driving metabolic reprogramming. CONCLUSIONS: This study establishes a robust LRL-based prognostic model and identifies AC026412.3 as a key regulator of lipid metabolic reprogramming via the SLC22A5-fatty acid β-oxidation axis, highlighting its potential as a biomarker and therapeutic target in HCC.
HCC↗
A population survival model for breast cancer.
Breast cancer is a major health problem, and disease control depends on an effective healthcare system. A registry-based tool to monitor the quality of breast cancer care could be useful. The aim of this study was to develop a population survival model for breast cancer based on the Nottingham Prognostic Model (NPM). To this end, 1452 cases of breast cancer diagnosed in the Umbria Region, Italy, during the period 1994-1996 were studied. An extensive search for routinely available variants in prognosis and treatment was performed. In about 80% of cases complete information on factors included in the NPM was available. The Cox model was used to assess the prognostic value of study factors. Nodal stage was the most important prognostic factor. In women who did not undergo axillary dissection (17%) the risk of death was twice that in women with no affected nodes, but they received chemotherapy with the same frequency. Radiotherapy was also less frequently used in this group. Grading was a significant prognostic factor only when women over 80 were excluded. Population survival models based on data from cancer registries may provide a tool that can be used to evaluate healthcare systems and the effectiveness of interventions. The inclusion of older women in our models decreased the significance of many established prognostic factors because of the frequency of incomplete evaluation and less aggressive treatment in these patients. Not undergoing surgical axillary dissection was associated with a worse prognosis and with less aggressive treatment.
Aged↗
A new measure of prognostic separation in survival data.
Multivariable prognostic models are widely used in cancer and other disease areas, and have a range of applications in clinical medicine, clinical trials and allocation of health services resources. A well-founded and reliable measure of the prognostic ability of a model would be valuable to help define the separation between patients or prognostic groups that the model could provide, and to act as a benchmark of model performance in a validation setting. We propose such a measure for models of survival data. Its motivation derives originally from the idea of separation between Kaplan-Meier curves. We define the criteria for a successful measure and discuss them with respect to our approach. Adjustments for 'optimism', the tendency for a model to predict better on the data on which it was derived than on new data, are suggested. We study the properties of the measure by simulation and by example in three substantial data sets. We believe that our new measure will prove useful as a tool to evaluate the separation available-with a prognostic model.
Brain Neoplasms↗
Blood transfusion and prognosis in Dukes' B and C colorectal cancer.
To evaluate the prognostic influence of blood transfusion in cancer patients, transfusion data were reviewed on 468 radically operated patients (260 Dukes' B and 208 Dukes' C) with carcinoma of the rectum and the rectosigmoid. Data on whole blood and packed red blood cell transfusions were recorded together with a number of clinical, pathological and histochemical characteristics. The endpoint used was death with cancer. All patients were followed for 2-7 years or until time of death. Univariate statistical methods revealed a highly significant trend towards worsened prognosis with increasing volume of transfusion blood. However, this effect was insignificant when multivariate statistical methods were employed: patients receiving whole blood or packed red blood cell transfusions did no worse than expected from their clinico-pathological characteristics. It is concluded that in this series the observed association between transfusion status and prognosis is adequately explained by a multivariate prognostic model including well-established prognostic factors.
Aged↗
Prospectively validated prediction of organ failure and hypotension in patients with septic shock: the Systemic Mediator Associated Response Test (SMART).
Conventional outcomes research provides only percentage risk categories that are not applicable to individual patients, and it predicts only mortality, utilization of resources and/or broad groupings of multiple organ system dysfunction. The purpose of the present study was to determine whether or not the Systemic Mediator Associated Response Test (SMART) methodology could identify interactions among demographics, physiologic parameters, standard hospital laboratory tests, and circulating cytokine concentrations to predict continuous and dichotomous dependent clinical variables, in advance, in individual patients with septic shock and to integrate these into prospectively validated models. Two hundred forty (240) patients with septic shock who were entered into the placebo arm of a multi-institutional clinical trial were randomly separated into a model building training cohort (n = 154) and a predictive cohort (n = 86), which was used to prospectively validate the prognostic models built upon the training cohort database. From baseline patient demographics; hospital laboratory tests; and plasma levels of interleukin-6, interleukin-8, and granulocyte colony stimulating factor, multiple regression models were developed that predicted clinically important continuous dependent variables quantitatively in individual patients. Multivariate stepwise logistic regression was utilized to develop models that prognosticated dichotomous dependent end points. At the completion of the modeling process, baseline data from individual patients in the predictive cohort was inserted into each multivariate model for each day. Prospective validation was accomplished by simple linear regression of individual predicted versus observed values for continuous dependent variables, and by establishing the Receiver Operator Characteristics Area Under the Curve (ROC AUC) for logistic regression models that predicted dichotomous end points. Through seven days, SMART quantitative predictions of selected physiologic and metabolic parameters were validated at r > 0.500 in 51%. Up to seven days after baseline, 31/49 (63%) SMART models for renal and liver function indicators were validated prospectively at the r > 0.700 level. For hematologic/coagulation models, 37/56 (66%) up to seven days had r > 0.900. Among dichotomous models, ROC AUC > 0.700 was achieved in 30/49 (61%) during the first week. SMART integration of demographics, bedside physiology, hospital laboratory tests, and circulating cytokines predicts organ failure and physiologic function indicators in individual patients with septic shock.
Area Under Curve↗
A behavioral rating scale as a predictor for survival of demented nursing home patients.
As part of a study towards determinants of survival in nursing home patients with dementia, the prognostic value of a behavioral rating scale for nursing home patients is assessed in an 8-year follow-up study. The 2-year survival rate for the entire cohort (n = 569) was 56%. Women (n = 459) had a 2-year survival rate of 62%, and men (n = 110) had a 2-year survival rate of 40%. Items indicating physical impairment, dependency and apathy had most prognostic value. Items measuring aggressive or depressive behavior, and cognitive impairment were less predictive. These results were confirmed in a multivariate proportional hazards analysis. A prognostic model with age, gender and five behavioral items (needs help when walking, occupied in useful activity, restless at night, utters physical complaints, and socializes with other patients) substantially differentiated in survival chances in patients with dementia. The model gives a predicted 2-year survival chance of less than 20% or more than 80% in 80 of the 569 patients. When adjusted for the variables in the model, previous residence had no prognostic value anymore. Possibilities for further work in this area of research are discussed.
Journal Article↗
Long-term ursodeoxycholic acid therapy for primary biliary cirrhosis: a follow-up to 12 years.
BACKGROUND: It is uncertain whether ursodeoxycholic acid therapy slows down the progression of primary biliary cirrhosis, according to two meta-analyses. However, the randomized trials evaluated had only a median of 24 months of follow-up. AIM: To evaluate long-term ursodeoxycholic acid therapy in primary biliary cirrhosis. METHODS: We evaluated 209 consecutive primary biliary cirrhosis patients, 69 compliant with ursodeoxycholic acid and 140 untreated [mean follow-up 5.79 (s.d. = 4.73) and 4.87 (s.d. = 5.21) years, respectively] with onset of all complications documented. Comparison was made following adjustment for baseline differences according to Cox modelling, Mayo and Royal Free prognostic models. RESULTS: Bilirubin and alkaline phosphatase concentrations improved with ursodeoxycholic acid (at 36 months, P = 0.007 and 0.018, respectively). Unadjusted Kaplan-Meier analysis showed benefit (P = 0.028), as 44 (31%) untreated and 15 (22%) ursodeoxycholic acid patients died or had liver transplantation. However, there was no difference when adjusted by Cox modelling (P = 0.267), Mayo (P = 0.698) and Royal Free models (P = 0.559). New pruritus or fatigue or other complications were not different, either before or after adjustment for baseline characteristics. CONCLUSIONS: Long-term ursodeoxycholic acid therapy did not alter disease progression in primary biliary cirrhosis patients despite a significant improvement in serum bilirubin and alkaline phosphatase consistent with, and similar to, those seen in ursodeoxycholic acid cohorts in randomized trials.
Adult↗
Prognostic factors in elderly patients with acute myeloid leukaemia.
Acute myeloid leukaemia (AML) is predominantly a disease of the elderly; the median age of incidence is 64 years, and 60% of all cases are over 60. With improved chemotherapy regimens and maximal supportive care, remission rates of up to 60% may be achieved in selected elderly patients. Whilst intensive chemotherapy is the treatment of choice for fit patients, it may be inappropriate for debilitated patients with poor prognosis disease in whom supportive care or palliative chemotherapy may be more suitable. AML in the elderly exhibits biological differences from AML in younger patients, and elderly patients may be unable to withstand the rigors of the intensive treatment regimens given to younger patients. We review methods to evaluate prognostic factors, the development and application of prognostic models, and available data regarding prognostic factors in elderly patients with AML. We discuss a rationale for the use of prognostic factors in selecting therapy for patients and for tailoring of therapy according to disease and host related variables.
Adolescent↗
Multi-omics dynamic profiling reveals predictive biomarkers for first-line immunochemotherapy in extensive-stage small-cell lung cancer.
BACKGROUND: Extensive-stage small-cell lung cancer (ES-SCLC) is associated with a poor prognosis. Although first-line immunochemotherapy improves clinical outcomes, robust prognostic biomarkers for this treatment modality remain unavailable. The aim of this study was to identify non-invasive, easily accessible, and dynamically monitored biomarkers of ES-SCLC by machine learning integrating serum metabolomics, lipidomics, and proteomics at multiple time points. METHODS: A total of 816 serum samples were collected from ES-SCLC patients receiving first-line immunotherapy combined with chemotherapy or first-line chemotherapy for metabolomics, lipidomics, and proteomics analysis. The immunochemotherapy cohort was randomly divided into training and validation subsets at a 6:4 ratio. Biomarkers were identified using machine learning algorithms, and their prognostic significance was evaluated through receiver operating characteristic (ROC) analysis, Kaplan–Meier survival analysis, and multivariate Cox regression. Potential metabolic pathways and mechanisms were further explored via integrated multi-omic analysis. RESULTS: The immunochemotherapy exhibited a prolonged median progression-free survival (PFS) and higher objective response rate (ORR) compared to the chemotherapy group. A total of 5 serum metabolites (uric acid, L-aspartate-semialdehyde, dimethisterone, xanthine, L-cysteine), 6 lipids (Cer d18:1/26:0, Cer d18:2/25:0, SM d18:1/20:1, SM d17:1/25:1, DG O-18:1_16:0, PS 18:0_24:0), and 3 proteins (ACIN1, ACSL4, PHGDH) were identified and constructed into independent prognostic models. Among patients receiving immunochemotherapy, those categorized as low-risk based on the model demonstrated significantly longer PFS compared with those in the high-risk group. These prognostic signatures also retained predictive value in patients who underwent second-line treatment with anlotinib plus immunochemotherapy. Integrated analysis revealed that glycine, serine, and threonine metabolism was the commonly enriched pathway across all three omics layers. Notably, PHGDH (protein), L-aspartate-semialdehyde and L-cysteine (metabolites), and PS (18:0_24:0) (lipid), key elements in this pathway, were all incorporated in the predictive model. In addition, models of the composition of these substances after one cycle of treatment can still predict the prognosis of patients. CONCLUSION: In this study, we constructed and validated a set of non-invasive, dynamically monitorable prognostic models (containing 5 metabolites, 6 lipids, and 3 proteins) using machine learning by integrating multiple time point data from the serum metabolome, lipid panel, and proteome to accurately distinguish the prognostic risk of patients with ES-SCLC receiving immunochemotherapy. PFS was significantly prolonged in patients in the low-risk group, and this model remains predictive in the subsequent second-line treatment with anlotinib in combination with immunochemotherapy. Glycine-serine-threonine metabolic pathway may be the key mechanism, of which PHGDH, L-aspartate semialdehyde, L-cysteine and PS (18:0_24:0) are the core predictors. This study provides the first multi-omics dynamic prognostic tool for ES-SCLC immunochemotherapy and reveals potential therapeutic targets.
Humans↗
Comparison of diagnostic usefulness of predictive models in preliminary differentiation of adnexal masses.
The purpose of this study was to compare prognostic models evaluating the probability of an ovarian cancer occurrence based on a number of clinical and ultrasonographic data in women with adnexal masses. A total of 686 women with adnexal masses underwent the examinations between 1994 and 2002. The recorded parameters included: age, menopausal status, body mass index, the grayscale and Doppler ultrasonographic examination, and selected markers concentration levels. In order to find the best combination of features, which significantly influences the probability of malignancy, stepwise logistic regression analysis, as well as artificial neural network, was used. The diagnostic efficiency of received models was estimated and compared using receiver-operating characteristics (ROC) curve. The results indicate that 431 and 255 patients had a benign and malignant ovarian tumor, respectively. Application of stepwise logistic regression analysis revealed statistically significant importance of eight features. The sensitivity and specificity for the received model were 65.71% and 77.59%, respectively. Three-layer perceptron network shows 13 features as significant predictors of malignancy. The network gave a sensitivity of 85.7% and specificity of 93.1%. Comparison of area under ROC curve for received models was 0.9679 vs 0.9716. Prognostic values of the analyzed neural model are not optimal but seem to surpass logistic regression model in terms of the predictive possibilities.
Adult↗
Fulminant hepatitis A virus infection in the United States: Incidence, prognosis, and outcomes.
Acute liver failure (ALF) due to hepatitis A virus (HAV) infection is an uncommon but potentially lethal illness. The aim of this study was to identify readily available laboratory and clinical features associated with a poor prognosis among ALF patients with HAV infection. The presenting features of 29 adults with anti-HAV IgM positive ALF enrolled in the ALFSG_between 1998 and 2005 were reviewed. The HAV patients listed for transplantation by UNOS were also reviewed. Acute HAV accounted for 3.1% of patients enrolled in the ALFSG. At 3 weeks follow-up, 16 had spontaneously recovered (55%), 9 underwent transplantation (31%), and 4 had died (14%). A prognostic model incorporating 4 presenting features (serum ALT <2,600 IU/L, creatinine >2.0 mg/dL, intubation, pressors) had an AUROC for transplant/death of 0.899 which was significantly better than the King's College criteria (0.623, P = .018) and MELD scores (0.707, P = .0503). Between 1988 and 2005, the frequency of patients requiring liver transplantation for HAV in the UNOS database significantly decreased from 0.7 % to 0.1% (P < .001). In addition, the proportion of HAV cases enrolled in the ALFSG significantly decreased from 5% to 0.8% (P = .007). In conclusion, the frequency of HAV patients enrolling in the ALFSG and being listed for liver transplantation in the United States has declined in parallel. A prognostic index consisting of 4 clinical and laboratory features predicted the likelihood of transplant/death significantly better than other published models suggesting that disease specific prognostic models may be of value in non-acetaminophen ALF.
Adult↗
[Problems of clinical prognosis in endogenous diseases with predominant affective disorders in childhood].
Based on a ++clinico-statistical analysis of patients (n-159) with cyclothymia and schizophrenia with predominant affective symptomatology who fell ill in childhood and were followed up for 5 to 18 years the main tendencies of the disease course and different patterns of the personality dynamics were discovered, correlating with a number of the premorbid characteristics and the structure of the first attack. The mathematic treatment using the Boolean model enabled one to obtain a prognostic model which may form the basis for the expert system to objectively evaluate, specify and accelerate the process of individual forecasting in the endogenous affective syndromes in childhood. The author provides evidence for relativity of the alternative importance of the clinical signs whose genuine prognostic weight only becomes known in diverse combinations with the other signs.
Child↗
Perioperative complications, comorbidities, and survival in oral or oropharyngeal cancer.
OBJECTIVES: To establish the value of clinical factors in the prediction of perioperative complications and death in patients with oral and oropharyngeal carcinomas and to develop a new extended clinical severity staging system that combines patient and tumor factors. PATIENTS AND METHODS: A total of 530 patients with oral or oropharyngeal carcinomas submitted to surgical treatment were studied. Logistic regression was used to identify risk factors for perioperative complications, and the Cox proportional hazards regression model was used to establish independent prognostic factors. RESULTS: Daily alcohol consumption, smoking, sex, neck lump, earache, pain, dysphagia, weight loss, oral bleeding, odynophagia, body mass index, National Cancer Institute comorbidity index score, American Society of Anesthesiologists surgical risk, hematocrit level, and total lymphocyte count had an impact on prognosis in univariate analysis. Survival according to extended clinical severity stage was 76.7% for stage 1, 64.4% for stage 2, 44.8% for stage 3, and 25.5% for stage 4 (chi( 2) = 64.16; P<.001). In multivariate analysis, only APACHE II score, neck dissection, POSSUM index score, and type of reconstruction were independent risk factors for perioperative complications. The final prognostic model included development of local plus systemic complications, extended clinical severity stage, type of reconstruction, and APACHE II score. CONCLUSIONS: Clinical variables have a predictive effect on morbidity and mortality of patients with oral and oropharyngeal cancer treated surgically. Local plus systemic perioperative complications can adversely affect the prognosis. The uniformity of results confirms that survival estimates can be enhanced by the addition of clinical characteristics to the TNM classification, creating a more accurate system for the estimation of prognosis.
Adult↗
Histopathologic, stereologic, epidemiologic, and clinical parameters in the prognostic evaluation of squamous cell carcinoma of the oral cavity.
BACKGROUND: Prognostic indicators that could assist in a more precise selection of patients with oral cancer for differentiated therapy would be clinically valuable. METHODS: A consecutive series of 161 cases of intraoral squamous cell carcinoma (SCC) occurring during a 5-year period in a population of 1.4 million inhabitants, was evaluated by histopathologic (the modified classification of Jakobsson et al.), stereologic, clinical, and epidemiologic parameters and the serum markers hemoglobin and rhesus blood group. RESULTS: Univariate analysis established a significant prognostic value in terms of cause-specific survival for T stage (P < .0001), stage (P < .0001), maximum tumor diameter (P < .0001), N stage (N+/NO) (P < .0001), alcohol consumption (P = .03), stereologic estimates of nuclear volume (P = .04), and the histomorphologic parameters mode of invasion (P = .001), pattern (P = .01), vascular invasion (P = .02), depth (P = .006), and mean histologic score. Tobacco consumption was borderline significant (P = .055). A multivariate analysis using the Cox proportional hazard analysis showed that both clinical (stage, P < .0001; size, P = .0027), epidemiologic (tobacco consumption, P = .0054), morphohistopathologic (mode of invasion P < .0001), and stereologic (nuclear volume, P = .0010) parameters had an independent significant effect on survival. Inversely, the mean histologic score had no prognostic value. From the final regression model prognostic forecasts were calculated. Twelve patients (25%) with stage I disease had unfavorable histologic and stereologic parameters. The observed survival (+/- 1 standard error of the estimate) for these patients was 33% +/- 18%. The observed survival for stage I patients with more favorable histologic and stereologic characteristics (n = 36) was 76% +/- 8%. CONCLUSION: The use of a combination of clinical, histologic, epidemiologic, and stereologic parameters will assist the design of treatment strategies for intraoral SCC.
Alcohol Drinking↗
The combination of gemcitabine and carboplatin as first-line treatment in patients with advanced urothelial carcinoma. A Phase II study of the Hellenic Cooperative Oncology Group.
BACKGROUND: The toxicity of platinum-based combinations represents a common problem for patients with advanced urothelial carcinoma. The authors previously reported encouraging efficacy for the combination of carboplatin and gemcitabine in patients considered to be unfit for cisplatin-based treatment. The objective of the current multicenter Phase II study was to evaluate the safety and efficacy of the combination of gemcitabine and carboplatin as first-line treatment in unselected patients with advanced urothelial carcinoma. METHODS: Patients with previously untreated, bidimensionally measurable, inoperable or metastatic urothelial carcinoma were treated with carboplatin, area under the concentration curve of 5 (Day 1) and gemcitabine at a dose of 1000 mg/m(2) (Days 1 and 8), every 21 days for a total of 6 cycles. RESULTS: Sixty patients (49 men and 11 women, with a median age of 69 yrs) were enrolled in the current study. Intent-to-treat analysis demonstrated an objective response rate (ORR) of 38.4% (95% confidence interval [95% CI], 26-51.8%) (11.7% complete responses and 26.7% partial responses). The median time to disease progression was 7.6 months (95% CI, 4.5-10.7 mos) and the median overall survival was 16.3 months (95% CI, 12-20.6 mos). The median survival was comparable to that reported for the combination of methotrexate, vinblastine, doxorubicin, and cisplatin (M-VAC) according to the Memorial Sloan-Kettering Cancer Center prognostic model for patients with similar baseline prognostic features. Grade 3 or 4 toxicity (according to the National Cancer Institute Common Toxicity Criteria [version 2.0]) included anemia (18%), thrombocytopenia (23%), and neutropenia (52%), with 7 episodes of febrile neutropenia (11%) reported. Nonhematologic toxicity was rare. One toxic death occurred during the study. CONCLUSIONS: The combination of gemcitabine and carboplatin appears to have considerable activity as the first-line treatment of unselected patients with advanced urothelial carcinoma with manageable toxicity, and deserves further evaluation in this setting.
Aged↗