Dataset Information

Treatment and overall survival in renal cell carcinoma: a Swedish population-based study (2000-2008).

ABSTRACT: This retrospective register study assessed overall survival (OS) and influential factors on OS in Swedish renal cell carcinoma (RCC) patients.Using three merged national health registers, Cox proportional-hazards analysis was conducted and, in three models, it was used to assess the impact of cytokine (interferon-? and tyrosine kinase inhibitor (TKI; sunitinib or sorafenib) treatment on OS in metastatic (m)RCC.From 2000 to 2008, 8009 patients were diagnosed with RCC and 2753 with mRCC (2002-2008). Median OS in RCC patients diagnosed from 2006 to 2008 compared with 2000-2005 was not reached vs 47.9 months (P<0.001), and in mRCC patients diagnosed from 2006 to 2008 compared with 2002-2005, was 12.4 vs 9.6 months, respectively (P=0.004). Factors associated with significantly improved OS in RCC were female gender, lower age, and previous nephrectomy, and, in mRCC female gender, previous nephrectomy, and any TKI prescription (Model 1: median-adjusted OS, 19.4 months (TKI patients) vs 9.7 months (non-TKI patients); hazard ratio, 0.621; P<0.001).OS was improved in Swedish patients diagnosed with RCC and mRCC in the period 2006-2008 compared with 2000-2005 (RCC) and 2002-2005 (mRCC). Although multifactorial in origin, results suggest that increased nephrectomy rates and the use of TKIs contributed to the improvement seen in mRCC patients.

SUBMITTER: Wahlgren T

PROVIDER: S-EPMC3629428 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Treatment and overall survival in renal cell carcinoma: a Swedish population-based study (2000-2008).

Wahlgren T T Harmenberg U U Sandström P P Lundstam S S Kowalski J J Jakobsson M M Sandin R R Ljungberg B B

British journal of cancer 20130326 7

<h4>Background</h4>This retrospective register study assessed overall survival (OS) and influential factors on OS in Swedish renal cell carcinoma (RCC) patients.<h4>Methods</h4>Using three merged national health registers, Cox proportional-hazards analysis was conducted and, in three models, it was used to assess the impact of cytokine (interferon-α and tyrosine kinase inhibitor (TKI; sunitinib or sorafenib) treatment on OS in metastatic (m)RCC.<h4>Results</h4>From 2000 to 2008, 8009 patients we ...[more]

PMID: 23531701

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Project description:Background and objectivesInvestigations of the prognosis are vital for better patient management and decision-making in patients with advanced metastatic renal cell carcinoma (mRCC). The purpose of this study is to evaluate the capacity of emerging Artificial Intelligence (AI) technologies to predict three- and five-year overall survival (OS) for mRCC patients starting their first-line of systemic treatment.Patients and methodsThe retrospective study included 322 Italian patients with mRCC who underwent systemic treatment between 2004 and 2019. Statistical analysis included the univariate and multivariate Cox proportional-hazard model and the Kaplan-Meier analysis for the prognostic factors' investigation. The patients were split into a training cohort to establish the predictive models and a hold-out cohort to validate the results. The models were evaluated by the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. We assessed the clinical benefit of the models using decision curve analysis (DCA). Then, the proposed AI models were compared with well-known pre-existing prognostic systems.ResultsThe median age of patients in the study was 56.7 years at RCC diagnosis and 78% of participants were male. The median survival time from the start of systemic treatment was 29.2 months; 95% of the patients died during the follow-up that finished by the end of 2019. The proposed predictive model, which was constructed as an ensemble of three individual predictive models, outperformed all well-known prognostic models to which it was compared. It also demonstrated better usability in supporting clinical decisions for 3- and 5-year OS. The model achieved (0.786 and 0.771) AUC and (0.675 and 0.558) specificity at sensitivity 0.90 for 3 and 5 years, respectively. We also applied explainability methods to identify the important clinical features that were found to be partially matched with the prognostic factors identified in the Kaplan-Meier and Cox analyses.ConclusionsOur AI models provide best predictive accuracy and clinical net benefits over well-known prognostic models. As a result, they can potentially be used in clinical practice for providing better management for mRCC patients starting their first-line of systemic treatment. Larger studies would be needed to validate the developed model.

Project description:ImportanceAnaplastic thyroid carcinoma (ATC) historically has a 4-month median overall survival (OS) from time of diagnosis, with disease-specific mortality approaching 100%. The association between recent major advancements in treatment and OS has yet to be evaluated.ObjectiveTo evaluate rates of OS in patients with ATC over the last 2 decades.Design, setting, and participantsRetrospective cohort study in a single tertiary care institution. Patients with histopathological confirmation of ATC from January 2000 to October 2019 were included and divided into 3 groups according to date of presentation: 2000-2013, 2014-2016, and 2017-2019.Main outcomes and measuresOverall survival compared among different treatment eras and differing therapies, including targeted therapy, immunotherapy, and surgery.ResultsOf 479 patients (246 men [51%]; median age, 65.0 [range, 21.1-92.6] years) with ATC evaluated, 52 (11%) were stage IVA, 172 (36%) stage IVB, and 255 (53%) stage IVC at presentation. The median OS of the entire cohort was 0.79 years (9.5 months), ranging from 0.01 to 16.63. The OS at 1 and 2 years was 35% (95% CI, 29%-42%) and 18% (95% CI, 13%-23%) in the 2000-2013 group (n = 227), 47% (95% CI, 36%-56%) and 25% (95% CI, 17%-34%) in the 2014-2016 group (n = 100), and 59% (95% CI, 49%-67%) and 42% (95% CI, 30%-53%) in the 2017-2019 group (n = 152), respectively (P < .001). The hazard ratio was 0.50 (95% CI, 0.38-0.67) for the 2017-2019 group compared with the 2000-2013 patients (P < .001). Factors associated with improved OS included targeted therapy (hazard ratio, 0.49; 95% CI, 0.39-0.63; P < .001), the addition of immunotherapy to targeted therapy (hazard ratio, 0.58; 95% CI, 0.36-0.94; P = .03), and surgery following neoadjuvant BRAF-directed therapy (hazard ratio, 0.29; 95% CI, 0.10-0.78; P = .02). Patients undergoing surgery following neoadjuvant BRAF-directed therapy (n = 20) had a 94% 1-year survival with a median follow-up of 1.21 years.Conclusion and relevanceIn this large single-institution cohort study spanning nearly 20 years, changes in patient management appear to be associated with significant increase in survival. The era of untreatable ATC is progressively being replaced by molecular-based personalized therapies, with integration of multidisciplinary therapies including surgery and radiation therapy.

Project description:BackgroundTo establish and validate nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in patients with papillary renal cell carcinoma (pRCC).MethodsPatients diagnosed with pRCC between 2010 and 2014 in the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively included in this study and divided into training and validation groups randomly. Uni- and multivariate Cox regression analyses were used to identify significant variables related to OS and CSS in the training group. Based on results of multivariate Cox regression analysis, nomograms for 3- and 5-year CSS and OS were established, respectively. Additionally, Kaplan-Meier (KM) survival curves were produced to learn the actual effects of different variables. Finally, the nomograms were evaluated both in the training group and the validation group using the area under the receiver operating characteristic (ROC) curve, the concordance index (C-index) and calibration curves.ResultsA total of 4,859 eligible patients were enrolled, with 3,403 categorized into the training group and 1,456 into the validation group. Seven factors [age, T stage, N stage, M stage, use of surgery/lymph node removal (LNR) and insurance status] were significantly related to OS and seven factors (age, T stage, N stage, M stage and use of surgery/chemotherapy/LNR) were significantly associated with CSS. These factors were eventually included in the predictive nomograms. The C-indexes for OS in the training and validation groups were 0.764 and 0.723 respectively, and 0.859 and 0.824 for CSS. The 3- and 5-year AUCs for OS were 0.779 and 0.752 in the training cohort, and 0.749 and 0.722 in the validation cohort. Similarly, 3- and 5-year AUCs for OS were 0.871 and 0.844 in the training cohort, and 0.853 and 0.822 in the validation group. Finally, the calibration curves suggested that the predictive nomograms had a good consistency between the observed and the predicted survival.ConclusionsIt was the first time to develop nomograms to predict the survival outcomes of pRCC patients. The prognostic nomograms were reliable with high accuracy, which might have guiding significance for clinical practice.

Project description:Renal-cell carcinoma (RCC) affects over 330,000 new patients every year, of whom 1/3 present with metastatic RCC (mRCC) at diagnosis. Most mRCC patients treated with a first-line agent relapse within 1 year and need second-line therapy. The present study aims to compare overall survival (OS) between nivolumab and cabozantinib from two recent pivotal studies comparing, respectively, each one of the two emerging treatments against everolimus in patients who relapse following first-line treatment. Comparison is traditionally carried out using the Bucher method, which assumes proportional hazard. Since OS curves intersected in one of the pivotal studies, models not assuming proportional hazards were also considered to refine the comparison. Four Bayesian parametric survival network meta-analysis models were implemented on overall survival (OS) data digitized from the Kaplan-Meier curves reported in the studies. Three models allowing hazard ratios (HR) to vary over time were assessed against a fixed-HR model. The Bucher method favored cabozantinib, with a fixed HR for OS vs. nivolumab of 1.09 (95% confidence interval: [0.77, 1.54]). However, all models with time-varying HR showed better fits than the fixed-HR model. The log-logistic model fitted the data best, exhibiting a HR for OS initially favoring cabozantinib, the trend inverting to favor nivolumab after month 5 (95% credible interval <1 from 10 months). The initial probability of cabozantinib conferring superior OS was 54%, falling to 41.5% by month 24. Numerical differences in study-adjusted OS estimates between the two treatments remained small. This study evidences that HR for OS of nivolumab vs. cabozantinib varies over time, favoring cabozantinib in the first months of treatment but nivolumab afterwards, a possible indication that patients with poor prognosis benefit more from cabozantinib in terms of survival, nivolumab benefiting patients with better prognosis. More evidence, including real-world observational data, is needed to compare effectiveness between cabozantinib and nivolumab.

Project description:ContextCurrent guidelines suggest several targeted therapies (TTs) and immunotherapies (ITs) in the treatment of advanced or metastatic renal cell carcinoma (mRCC). Ideal sequencing of these treatments is unclear.ObjectiveThe primary objective was to evaluate the overall survival (OS) data of the treatments approved for mRCC. Secondary objectives included evaluating other signs of efficacy and adverse events.Evidence acquisitionWe reviewed the current Food and Drug Administration-approved treatments for mRCC. Trials associated with approval were reviewed. We also included pre- and postapproval publications when appropriate.Evidence synthesisThere is minimal evidence supporting OS benefit for the nine approved TTs. They result in adverse events and are a considerable economic burden. For these reasons, their future role in mRCC treatment should be re-evaluated, given the emergence of IT that have demonstrated OS benefits. Accumulating long-term survival data with high-dose interleukin-2 treatment suggests that this older treatment could still be considered for eligible patients. Checkpoint inhibitors have shown promising OS and durable responses; as such, the high cost of treatment might be justified. However, the available evidence does not suggest that adding TT to IT would increase efficacy over IT alone, but would add toxicity.ConclusionsTrial data supporting OS benefit are much stronger for ITs than for TTs. Combining checkpoint inhibitors with TTs has not been shown to produce better OS than checkpoint inhibitors alone, while more adverse events are present. Granting drug approvals based on efficacy without demonstrated OS benefit should be revisited.Patient summaryApproved treatments for metastatic kidney cancer include targeted and immune-based therapies. The former commonly produces temporary tumour shrinkage, but survival benefits are unclear. All approved immunotherapies have increased survival, and a proportion of patients appear cured.

Project description:BackgroundPapillary renal cell carcinoma (pRCC) is the largest histologic subtype of non-clear-cell RCC. To date, there is no reliable nomogram to predict the prognosis of patients with pRCC after nephrectomy. We aimed to first establish an effective nomogram to predict the overall survival (OS) of patients with pRCC after nephrectomy.MethodsA total of 3,528 eligible patients with pRCC after nephrectomy were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. The patients were randomized into the training cohort (n = 2,472) and the validation cohort (n = 1,056) at a 7:3 ratio. In total, 122 real-world samples from our institute (titled the AHMU-pRCC cohort) were used as the external validation cohort. Univariate and subsequent multivariate Cox regression analyses were conducted to identify OS-related prognostic factors, which were further used to establish a prognostic nomogram for predicting 1-, 3-, and 5-year OS probabilities. The performance of the nomogram was evaluated by using the concordance index (C-index), receiver operating characteristic curve (ROC), calibration plot, and decision curve analysis (DCA).ResultsMultivariate Cox analysis showed that age, race, marital status, TNM stage, tumor size, and surgery were significant OS-related prognostic factors. A prognostic model consisting of these clinical parameters was developed and virtualized by a nomogram. High C-index and area under the ROC curve (AUC) values of the nomogram at 1, 3, and 5 years were found in the training, validation, and AHMU-pRCC cohorts. The calibration plot and DCA also showed that the nomogram had a satisfactory clinical application value. A risk classification system was established to risk-stratify patients with pRCC.ConclusionBased on a large cohort from the public SEER database, a reliable nomogram predicting the OS of patients with pRCC after nephrectomy was constructed, which could optimize the survival assessment and clinical treatment.

Dataset Information

Treatment and overall survival in renal cell carcinoma: a Swedish population-based study (2000-2008).

Publications

Treatment and overall survival in renal cell carcinoma: a Swedish population-based study (2000-2008).

Similar Datasets

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