Changeable prognosis and associated prognostic factors for conditional survival estimates in metastatic renal cell carcinoma patients receiving the first-line targeted therapy.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 587-587
Author(s):  
Minyong Kang ◽  
Hyun Hwan Sung ◽  
Hwang Gyun Jeon ◽  
Byong Chang Jeong ◽  
Se Hoon Park ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Targeted Therapy ◽  
Predictive Factors ◽  
Initial Treatment ◽  
Conditional Survival ◽  
First Line ◽  
Cox Regression Analysis ◽  
Survival Estimation ◽  
Tki Treatment ◽  
Over Time

587 Background: Conditional survival (CS) indicates the probability that patient would survive additional periods, given that the patients has previous survivorship after diagnosis or initial treatment. Here, we aim to evaluate the CS probabilities in mRCC patients who underwent targeted therapy with tyrosine kinase inhibitors (TKI) and to identify the significant prognostic factors of the CS over time. Methods: A total of 1,498 mRCC patients receiving 1st line TKI was finally analyzed from Korean multicenter database of mRCC. Kaplan-Meier survival estimates was used to calculate overall and cancer-specific CS rates by using following formula: CS(α│β) = S(α+β)/S(β), where CS(α│β) indicates the likelihood of additional α years survivorship in the person who has already survived for β years after initial diagnosis or treatment, and S(χ) is the actual survival rate. The Cox regression analysis was used to determine the predictors of CS depended on clinicopathological features. Results: We observed that 1, 2, 3, 4, and 5-year conditional cancer-specific survival (CSS) gradually increased as patients who have all additional survivorships after initial treatment, compared to those with baseline survival estimation. Also, 1, 2, 3, 4, and 5-year conditional OS rates also increased after additional 1, 2, 3, 4, and 5 year survivorships following first-line TKI treatment. Furthermore, we found that key predictive factors of OS and CSS were changed over time in multivariate analysis. While several variables, such as BMI, histologic subtypes, pT stage, were identified as prognosticators of CSS at baseline, they were not remained as independent predictors after 1 yr survivorship. Conversely, only previous metastatectomy was determined as a key prognostic factor for conditional OS over time until 4 yr survivorship after initial TKI treatment. Conclusions: Our study offers valuable information for practical survival estimation and relevant predictive factors for patients with mRCC receiving targeted therapy.

HSR19-090: Changes in Adherence to Tyrosine Kinase Inhibitor Treatment Patterns Among Patients With Chronic Myeloid Leukemia and the Impact on Costs: 2001–2017

2019 ◽  
Vol 17 (3.5) ◽  
pp. HSR19-090
Author(s):  
Henry J. Henk ◽  
Lena E. Winestone ◽  
Jennifer J. Wilkes ◽  
Laura Becker ◽  
Pamela Morin ◽  
...  
Keyword(s):  
Health Care ◽  
Chronic Myeloid Leukemia ◽  
Healthcare Costs ◽  
Myeloid Leukemia ◽  
First Line ◽  
Tki Treatment ◽  
The Impact ◽  
Care Costs ◽  
Over Time ◽  
Privately Insured

Background: Chronic myeloid leukemia (CML) treatment improved considerably after introduction of oral tyrosine kinase inhibitors (TKI). As a result, the number of patients living with CML may reach 250,000 by 2040. We track changes in TKI treatment adherence since 2001 and provide an early assessment of treatment costs following the availability of second-generation TKIs and generic imatinib. Methods: A retrospective cohort from the OptumLabs Data Warehouse, which includes claims data for privately insured and Medicare Advantage (MA) enrollees in a large private U.S. health plan with medical and pharmacy benefits, was used. Patients with CML initiated TKI treatment between May 2001 and October 2016 and were continuously enrolled in the health plan 6 months prior through 12 months following TKI start. Adherence was defined by medication possession ratio (MPR1=total days’ supply of imatinib in 1st year divided by 365, 1=perfect adherence). Total health care costs include medical and prescription medication benefits. MPR1 was modeled using ordinary least squares regression. The association between MPR1 and healthcare costs was estimated using a generalized linear model specified with a gamma error distribution and a log link. Results: We identified 1,793 eligible patients. First-line TKI has changed over time (dasatinib and nilotinib represent 45% of all 2016 starts; imatinib 55%). From 2001 to 2016, adherence increased (Table 1). MPR1 was higher in men and increased with age until age ∼62 after which it declined. MPR1 was lower for patients with more comorbid conditions prior to treatment. Overall, MPR1 was inversely associated with total health care costs (medical and pharmacy) among privately insured (P<.001) but not MA enrollees. The net impact of MPR1 on total healthcare costs diminished over time (P<.001) where a 10% point decrease in MPR1 was associated with 12% and 4% lower total costs, prior to and following availability of 2nd generation TKIs, respectively. When examining medical costs only, MPR1 was inversely associated with medical costs for both privately insured (P<.001) and MA enrollees (P=.016). Conclusions: We found that adherence to TKI treatment increased over time. While imatinib is still used more frequently than other TKIs as first-line therapy, second-generation TKIs are becoming increasingly used as first-line agents. Possible cost-offsets are decreasing over time but it may be too early to formally evaluate the impact of generic imatinib.

scholarly journals Conditional Survival after Trimodality Therapy for Esophageal Cancer: A Re-evaluation of Prognostic Factors Over Time

2021 ◽  
Vol 233 (5) ◽  
pp. S258
Author(s):  
Hope Feldman ◽  
Jiangong Niu ◽  
Nicolas Zhou ◽  
Wayne L. Hofstetter ◽  
Reza J. Mehran ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Prognostic Factors ◽  
Conditional Survival ◽  
Trimodality Therapy ◽  
Over Time

Prognostic and predictive factors in metastasic colorectal cancer.

2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 690-690
Author(s):  
Pilar Garcia Alfonso ◽  
Gonzalo Garcia ◽  
Iria Gallego ◽  
Isabel Peligros ◽  
Ana Corcuera ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Retrospective Study ◽  
Predictive Factors ◽  
Primary Tumor ◽  
Biological Treatment ◽  
Tumor Resection ◽  
Primary Tumor Resection ◽  
Wild Type ◽  
First Line ◽  
Prognostic And Predictive Factors

690 Background: In recent years, prognostic and predictive factors in mCRC are becoming more important, outstanding the tumor and metastasic location, the primary tumor and/or metastasis resections as well as molecular biomarkers (KRAS, NRAS, BRAF and PIK3CA). Methods: We conducted a retrospective study of 334 patients with mCRC diagnosticated between January 2010 and June 2015 in the Oncology Service from HGUGM. The objective of our study was to evaluate the overall survival (OS) relating to each of these settings. We also evaluated OS considering the biological treatment received in first line. Multivariant analysis was performed with independence of tumor and metastasic location, metastasectomies, no primary tumor resection, biological treatment used in first line, age, sex and moleculars biomarkers. Results: Median OS was 24,34m. The advantageous prognostic factors which statistically significant impact on the median OS have been triple (RAS and BRAF) (n = 86) and quadruple (RAS, BRAF and PIK3CA) (n = 76) wild-type (wt 36,6m vs mut 23m, p = 0,02; wt 37,6m vs mut 23,38m, p = 0.02, respectively), left tumor location with rectum (left 25,55m vs right 19,44m, p = 0,001) and isolated hepatic and pulmonary metastasic location (30,32 vs 23 m, p = 0,03; 45,32m vs 23,38 m, p = 0,004, respectively). The main disadvantageous prognostic factor has been the no primary tumor resection (13,75m vs 31,61m, p = 0,00001) with independence of synchronous presentation of the disease as well as biomarkers mutational status. Median OS in first line was 30.13 m with bevacizumab (n = 54) vs 16,18m with antiEGFR (n = 28) (p = 0.02) in extended RAS wild-type patients (n = 101). Considering the multivariate analysis, the independent prognostic factors have been the isolated pulmonary metastasis (HR = 0,46; CI 95% 0,30-0,73;p = 0,001), quadruple wild-type (HR = 0,69;CI 95% 0,49-0,97; p = 0,031), metastasectomies (HR = 0,29; CI 95% 0,21-0,4; p = 0,000), right location (HR = 1,43; CI 95% 1,08-1,9;p = 0,014) and no primary tumor resection (HR = 2,06; CI 95% 1,49-2,86; p = 0,000). Conclusions: Isolated pulmonary metastasis, quadruple wild-type, metastasectomies, left location and primary tumor resection have independent positive prognostic value, according to our retrospective study.

Surgical Resection is An Effective Therapy for Single Large Hepatocellular Carcinom

2021 ◽  
Author(s):  
Pojen Hsiao ◽  
Jen-Hao Yeh ◽  
Chao-Ming Hung ◽  
Hung-Yu Lin ◽  
TaoQian Tan ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Liver Disease ◽  
Surgical Resection ◽  
Initial Treatment ◽  
Cox Regression ◽  
Progression Free Survival ◽  
Therapeutic Strategies ◽  
Cox Regression Analysis ◽  
Class A ◽  
Kaplan Meier

Abstract Background Identifying prognostic factors and therapeutic strategies for single large hepatocellular carcinoma (HCC) is crucial. This retrospective study investigated prognostic factors in patients with single large HCC (≥5 cm) and Child–Pugh (CP) class A liver disease and recommended therapeutic strategies. Methods In total, 305 patients with single large HCC and CP class A liver disease but without distant metastasis or macrovascular invasion were included. Their clinicopathological data, overall survival (OS), and progression-free survival (PFS) were recorded. OS and PFS rates were analyzed using the Kaplan–Meier method and Cox regression analysis. Results In this study, 77.8% of the patients were men; the median age was 63 years. Approximately 34.1% of the patients had cirrhosis and 89.6% had CP class A5 disease. The most common initial treatment was resection (49.5%), followed by transarterial chemoembolization (TACE; 48.2%). OS and PFS rates 1, 5, and 10 years after initial treatment were 88.6%, 58.0%, and 46.8% and 73.6%, 48.2%, and 31.3%, respectively. OS and PRS rates were significantly higher in patients receiving surgical resection than in those receiving TACE. The 1-, 5-, and 10-year OS rates were 94.6%, 76.7%, and 66.7% after resection and 83.1%, 39.0%, and 26.6% after TACE. The 1-, 5-, and 10-year PRS rates were 82.5%, 55.7%, and 51.0% after resection and 64.3%, 40.5%, and 22.7% after TACE. In multivariate analysis, CP class A5/6 (A5 vs. A6; hazard ratio [HR]: 0.23; 95% confidence interval [CI]: 0.15–0.38, P < 0.001) and initial treatment (resection vs. TACE; HR: 0.22; 95% CI: 0.15–0.36, P < 0.001; resection vs. other treatments; HR: 0.37; 95% CI: 0.17–0.65, P = 0.016) were significantly associated with OS. In addition, CP class A5/6 (A5 vs. A6; HR: 0.32; 95% CI: 0.18–0.56, P < 0.001) and initial treatment (resection vs. TACE; HR: 0.30; 95% CI: 0.16–0.51, P < 0.001; resection vs. other treatments; HR: 0.51; 95% CI: 0.26–0.81, P = 0.042) were significantly associated with PFS. Conclusion Surgical resection achieved significantly higher OS and PRS rates than TACE. Surgical resection is an effective and safe therapy for single large HCC.

Conditional Survival Analysis in a Large Cohort of Multiple Myeloma Patients Provides Detailed Information about Long-Term Survival and Constitutes a Different Way to Identify Patients with Extended Life Expectancy

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 4982-4982
Author(s):  
Martina Kleber ◽  
Stefanie Hieke ◽  
Bernd Koch ◽  
Gabriele Ihorst ◽  
Ralph Wäsch ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Prognostic Factors ◽  
Initial Diagnosis ◽  
Large Cohort ◽  
Stage Ii ◽  
Disease Stage ◽  
Conditional Survival ◽  
Long Term Survivors ◽  
Over Time

Abstract Abstract 4982 Introduction: Prior analyses have advocated that mortality from major cancer has declined reflecting continuing progress in cancer prevention, early detection and treatment. Survival estimates are typically presented as the probability of surviving a given length of time after the diagnosis. In contrast, conditional survival describes the probabilities of surviving y additional years given patients survived x years. Conditional survival provides additional information about how the risk of death may change over time, taking into account, how long someone has already survived. In multiple myeloma many prognostic parameters have been proposed to predict survival, but results on conditional survival are still lacking. Methods: We evaluated 816 consecutive multiple myeloma patients treated at our department between 1997–2011. Patients' data were assessed via electronic medical record (EMR) retrieval within an innovative research data warehouse. Our platform, the University of Freiburg Translational Research Integrated Database Environment (U-RIDE), acquires and stores all patient data contained in the EMR at our hospital and provides immediate advanced text searching capacity. In an initial step, we assessed age, gender, disease stage (Durie&Salmon [D&S]), time of death and last follow-up. Moreover, we determined 5-year conditional survival as the probability of surviving at least 5 more years as a function of years a patient had already survived since initial diagnosis (i. e. 5-year conditional survival for those, who survived 0, 1, 2, 3, 4 and 5 years after initial diagnosis). Five year conditional survival was stratified according to gender, stage, age and other risk variables. Results: The OS probabilities at 5- and 10- years were 50% and 25%, respectively. The 5-year conditional survival probabilities remained almost constant over the years a patient had already survived after initial diagnosis (∼53%). According to baseline variables, conditional survival estimates showed no gender differences. As expected, D&S stage I vs. stage II+III showed substantially different 5-year conditional survival estimates over the years for those who survived 1 year after initial diagnosis (75% vs. 42%, respectively). Similarly, age subgroups <60, 60–70 and >70 years showed notably different 5-year conditional survival estimates, but also remained constant over the course of time with ∼63%, 51% and 27%, respectively. The multivariable Cox model, including gender, year of admission (before 2001, 2001–2007 and after 2007), D&S (stage II-III) and age (>70 years) showed increased hazard ratio (HR) for both latter groups of 2. 2 (95% CI 1. 8–2. 7; <0. 0001) and 3. 5 (95% CI: 2. 7–4. 4, <0. 0001), respectively. Ongoing analyses aim to distinctively identify long-term survivors via conditional survival. In order to obtain a comprehensive analysis of relevant prognostic factors, we have focused on variables with high degree of completeness. These include disease-related factors, such as single components of the D&S (e. g. hemoglobin, calcium, creatinine and osteolyses) and International Staging System, laboratory variables (e. g. LDH, type of paraprotein) and host-related risk factors. The latter include comorbid conditions such as performance status and organ function. Of note, over the study period, admission of patients <60 years decreased from 60% to 34%, but increased for those ≥70 years from 10% to 35%, respectively, illustrating that not only young and fit, but also elderly patients are increasingly treated within large referral and university centers and that patient cohorts and risks do not remain constant over time. Conclusions: In this study, involving a large cohort of multiple myeloma patients, analyses stratified by age and stage revealed substantially different conditional survival estimates. Conditional survival seems an attractive tool to predict outcome over time, supplements existing measures and may guide cancer survivors in planning their future. The combination of the main prognostic factors of the ongoing analysis in a multiple myeloma specific risk model, may define long-term survivors via conditional survival more distinctively and will be presented at the meeting. Disclosures: No relevant conflicts of interest to declare.

Prognostic and predictive factors for overall survival (OS) in metastatic esophagogastric cancer (EGC): A meta-analysis.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 4048-4048 ◽  
Author(s):  
Emil ter Veer ◽  
Jessy Joy van Kleef ◽  
Sandor Schokker ◽  
Stephanie Van Der Woude ◽  
Marety Laarman ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Predictive Factors ◽  
Meta Analysis ◽  
Performance Status ◽  
Disease Stage ◽  
First Line ◽  
Measurable Disease ◽  
Treatment Comparisons ◽  
Metastatic Sites ◽  
Prognostic And Predictive Factors

4048 Background: Prognostic and predictive factors for metastatic EGC are important to estimate prognosis, inform clinical decision-making and design future trials. We performed a systematic review with meta-analysis to identify these factors. Methods: We searched Medline, EMBASE and CENTRAL for phase 2/3 randomized controlled trials (RCTs) until January 2016 on palliative chemotherapy and targeted therapy for metastatic EGC. Prognostic and predictive factors were identified from respectively multivariate cox regressions and stratified treatment comparisons. Hazard Ratio’s (HR) for OS were extracted and pooled with meta-analysis if possible. Prognostic factors were considered independent if the multivariate HR was significant (P≤0.05). Predictive factors were clinically relevant if P for subgroup interaction was ≤0.20 and the HR in one of the subgroups was significant (P≤0.05). Results: We identified 47 RCTs (14,853 patients), wherein 54 potential prognostic and 40 predictive factors were reported. Eight independent prognostic factors for poor OS reported in ≥2 RCTs based on ≥300 patients were: performance status of ≥1 vs 0 (pooled HR, 95% confidence interval: 1.47, 1.25-1.73) or 2 vs 0-1 (1.52, 1.32-1.76); metastatic vs locally advanced disease (1.55, 1.39-1.72); diffuse vs intestinal/other histology (1.38, 1.12-1.71); ≥3 vs < 2 metastatic sites (1.35, 1.07-1.70); presence of metastases in peritoneum (1.24, 1.01-1.51) or liver (1.45 (1.28-1.64); measurable vs non-measurable disease (1.31, 1.04-1.66); and no prior vs prior surgery (1.33, 1.16-1.53). Predictive factors for specific treatment comparisons based on ≥300 patients were: age (≥65 vs < 65); performance status; tumor location (GEJ vs stomach); disease stage; number of metastatic sites; peritoneal metastasis; measurable disease; histology; HER2; KRAS; VEGF A; and Neuropilin-1 for first line treatments; and time to progression on first line therapy ( < 3, 3-6 or ≥6 months) for second-line treatments. Conclusions: Eight independent prognostic factors for OS and thirteen clinically relevant predictive factors for treatment efficacy of EGC were found.

Sign in / Sign up

Export Citation Format

Share Document