scholarly journals Evaluation of treatment-related mortality among paediatric cancer deaths: a population based analysis

2017 ◽  
Vol 116 (4) ◽  
pp. 540-545 ◽  
Author(s):  
Jason D Pole ◽  
◽  
Paul Gibson ◽  
Marie-Chantal Ethier ◽  
Tanya Lazor ◽  
...  
Keyword(s):  
Population Based ◽  
Paediatric Cancer ◽  
Treatment Related Mortality ◽  
Related Mortality

A Network of Treatment Centers and Standardisation of Treatment Protocol Leads to Reduction in Mortality in Acute Promyelocytic Leukemia (APL)

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 4317-4317 ◽  
Author(s):  
Anand P. Jillella ◽  
Farrukh Awan ◽  
Ravindra B. Kolhe ◽  
Jeremy M Pantin ◽  
Devi D Morrison ◽  
...  
Keyword(s):  
High Risk ◽  
High Mortality ◽  
Causes Of Death ◽  
Population Based ◽  
Low Risk ◽  
Recent Analysis ◽  
Cumulative Survival ◽  
Treatment Related Mortality ◽  
Related Mortality

Abstract Abstract 4317 Background: APL is widely accepted as a curable leukemia with most multi-institutional studies showing very low treatment related mortality. This is in contrast to treatment in clinical practice outside the study population where the treatment related mortality is higher. A few recent population based studies show that mortality maybe as high as 30% in APL patients during induction. A recent analysis of SEER data from 13 population-based cancer registries with 1400 APL patients in the US showed that 17% of all patients and 24% of patients greater than 55 years of age die within one month of diagnosis. Swedish registry data and Brazilian data also show this high mortality during induction. The most common causes of death are bleeding, infection, differentiation syndrome and multi-organ failure. Patients who survive induction have an excellent cure rate with few late relapses. Hence, decreasing early deaths is a high priority both at experienced as well as smaller centers with limited leukemia treatment experience in this highly curable disease. Methods: At Georgia Health Sciences University, between 7/2005 and 6/2009, 19 patients were diagnosed with APL. Seven patients (5 high-risk and 2 low-risk) died during induction resulting in an unusually high mortality rate of 37%. All patients who survived induction are still in remission at present. The high early death rate prompted us to develop a simple, 2 page treatment algorithm that focuses on quick diagnosis, prompt initiation of therapy, and proactive and aggressive management of all the major causes of death during induction. We also developed a network of physicians in smaller community based treatment centers and gave them access to our protocol and helped them manage these patients in the induction period with the hypothesis that this standardized treatment approach will result in decreasing induction mortality. Results: From 11/2010 to 7/2012, we treated 5 patients at GHSU and helped manage 4 patients at 2 outreach sites. The age range was 30 to 60; two patients were high-risk, 6 intermediate- and one low-risk. In the pre-algorithm cohort the cumulative survival was 63.1% at 1 year with all deaths happening within 31 days. In contrast, after the implementation of a standardized algorithm the cumulative survival was 100% with no deaths during the induction or subsequent follow-up period, log rank p-value=0.05, with a median follow-up of more than 4-years in surviving patients. Conclusions: While we recognize that this is a small cohort, our own experience and a similar approach pioneered by investigators in Brazil clearly shows that this centralized, algorithm-based management under the direct supervision of a leukemia expert can be an effective intervention to decrease early deaths in APL. Based on the Brazilian experience an international consortium was formed to reduce the mortality and interim data show a reduction in early mortality to 7.5% with this networking of treatment centers. We believe our experience warrants large scale implementation with development of a network of physicians and standardization of treatment in the United States to improve early outcomes in this highly curable leukemia. Disclosures: Awan: Allos Therapeutics: Speakers Bureau.

Temporal Trends in Mortality From Diseases of the Circulatory System After Treatment for Hodgkin Lymphoma: A Population-Based Cohort Study in Sweden (1973 to 2006)

2013 ◽  
Vol 31 (11) ◽  
pp. 1435-1441 ◽  
Author(s):  
Sandra Eloranta ◽  
Paul C. Lambert ◽  
Jan Sjöberg ◽  
Therese M.L. Andersson ◽  
Magnus Björkholm ◽  
...  
Keyword(s):  
Hodgkin Lymphoma ◽  
Causes Of Death ◽  
Excess Mortality ◽  
Temporal Trends ◽  
Circulatory System ◽  
Population Based ◽  
Competing Causes ◽  
Treatment Related Mortality ◽  
Related Mortality

PurposeHodgkin lymphoma (HL) survival in Sweden has improved dramatically over the last 40 years, but little is known about the extent to which efforts aimed at reducing long-term treatment-related mortality have contributed to the improved prognosis.MethodsWe used population-based data from Sweden to estimate the contribution of treatment-related mortality caused by diseases of the circulatory system (DCS) to temporal trends in excess HL mortality among 5,462 patients diagnosed at ages 19 to 80 between 1973 and 2006. Flexible parametric survival models were used to estimate excess mortality. In addition, we used recent advances in statistical methodology to estimate excess mortality in the presence of competing causes of death.ResultsExcess DCS mortality within 20 years after diagnosis has decreased continually since the mid-1980s and is expected to further decrease among patients diagnosed in the modern era. Age at diagnosis and sex were important predictors for excess DCS mortality, with advanced age and male sex being associated with higher excess DCS mortality. However, when accounting for competing causes of death, we found that excess DCS mortality constitutes a relatively small proportion of the overall mortality among patients with HL in Sweden.ConclusionExcess DCS mortality is no longer a common source of mortality among Swedish patients with HL. The main causes of death among long-term survivors today are causes other than HL, although other (non-DCS) excess mortality also persists for as long as 20 years after diagnosis, particularly among older patients.

scholarly journals Treatment-related mortality in newly diagnosed pediatric cancer: a population-based analysis

2018 ◽  
Vol 7 (3) ◽  
pp. 707-715 ◽  
Author(s):  
Paul Gibson ◽  
Jason D. Pole ◽  
Tanya Lazor ◽  
Donna Johnston ◽  
Carol Portwine ◽  
...  
Keyword(s):  
Pediatric Cancer ◽  
Population Based ◽  
Newly Diagnosed ◽  
Treatment Related Mortality ◽  
Related Mortality

scholarly journals Hepatitis C virus infection and risk of liver-related and non-liver-related deaths: a population-based cohort study in Naples, southern Italy

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Pierluca Piselli ◽  
Diego Serraino ◽  
Mario Fusco ◽  
Enrico Girardi ◽  
Angelo Pirozzi ◽  
...  
Keyword(s):  
Southern Italy ◽  
Population Based ◽  
Hcv Infection ◽  
Hcv Rna ◽  
Risk Of Death ◽  
High Prevalence ◽  
Specific Mortality ◽  
Chronic Hcv Infection ◽  
Chronic Hcv ◽  
Related Mortality

Abstract Background Hepatitis C virus (HCV) infection represents a global health issue with severe implications on morbidity and mortality. This study aimed to evaluate the impact of HCV infection on all-cause, liver-related, and non-liver-related mortality in a population living in an area with a high prevalence of HCV infection before the advent of Direct-Acting Antiviral (DAA) therapies, and to identify factors associated with cause-specific mortality among HCV-infected individuals. Methods We conducted a cohort study on 4492 individuals enrolled between 2003 and 2006 in a population-based seroprevalence survey on viral hepatitis infections in the province of Naples, southern Italy. Study participants provided serum for antibodies to HCV (anti-HCV) and HCV RNA testing. Information on vital status to December 2017 and cause of death were retrieved through record-linkage with the mortality database. Hazard ratios (HRs) for cause-specific mortality and 95% confidence intervals (CIs) were estimated using Fine-Grey regression models. Results Out of 626 deceased people, 20 (3.2%) died from non-natural causes, 56 (8.9%) from liver-related conditions, 550 (87.9%) from non-liver-related causes. Anti-HCV positive people were at higher risk of death from all causes (HR = 1.38, 95% CI: 1.12–1.70) and liver-related causes (HR = 5.90, 95% CI: 3.00–11.59) than anti-HCV negative ones. Individuals with chronic HCV infection reported an elevated risk of death due to liver-related conditions (HR = 6.61, 95% CI: 3.29–13.27) and to any cause (HR = 1.51, 95% CI: 1.18–1.94). The death risk of anti-HCV seropositive people with negative HCV RNA was similar to that of anti-HCV seronegative ones. Among anti-HCV positive people, liver-related mortality was associated with a high FIB-4 index score (HR = 39.96, 95% CI: 4.73–337.54). Conclusions These findings show the detrimental impact of HCV infection on all-cause mortality and, particularly, liver-related mortality. This effect emerged among individuals with chronic infection while those with cleared infection had the same risk of uninfected ones. These results underline the need to identify through screening all people with chronic HCV infection notably in areas with a high prevalence of HCV infection, and promptly provide them with DAAs treatment to achieve progressive HCV elimination and reduce HCV-related mortality.

Predictors of and Trends in High-Intensity End-of-Life Care Among Children With Cancer: A Population-Based Study Using Health Services Data

2017 ◽  
Vol 35 (2) ◽  
pp. 236-242 ◽  
Author(s):  
Alisha Kassam ◽  
Rinku Sutradhar ◽  
Kimberley Widger ◽  
Adam Rapoport ◽  
Jason D. Pole ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Health Services ◽  
High Intensity ◽  
Hematologic Malignancies ◽  
Population Based ◽  
Children With Cancer ◽  
Eol Care ◽  
Related Mortality

Purpose Children with cancer often receive high-intensity (HI) medical care at the end-of-life (EOL). Previous studies have been limited to single centers or lacked detailed clinical data. We determined predictors of and trends in HI-EOL care by linking population-based clinical and health-services databases. Methods A retrospective decedent cohort of patients with childhood cancer who died between 2000 and 2012 in Ontario, Canada, was assembled using a provincial cancer registry and linked to population-based health-care data. Based on previous studies, the primary composite measure of HI-EOL care comprised any of the following: intravenous chemotherapy < 14 days from death; more than one emergency department visit; and more than one hospitalization or intensive care unit admission < 30 days from death. Secondary measures included those same individual measures and measures of the most invasive (MI) EOL care (eg, mechanical ventilation < 14 days from death). We determined predictors of outcomes with appropriate regression models. Sensitivity analysis was restricted to cases of cancer-related mortality, excluding treatment-related mortality (TRM) cases. Results The study included 815 patients; of these, 331 (40.6%) experienced HI-EOL care. Those with hematologic malignancies were at highest risk (odds ratio, 2.5; 95% CI, 1.8 to 3.6; P < .001). Patients with hematologic cancers and those who died after 2004 were more likely to experience the MI-EOL care (eg, intensive care unit, mechanical ventilation, odds ratios from 2.0 to 5.1). Excluding cases of TRM did not substantively change the results. Conclusion Ontario children with cancer continue to experience HI-EOL care. Patients with hematologic malignancies are at highest risk even when excluding TRM. Of concern, rates of the MI-EOL care have increased over time despite increased palliative care access. Linking health services and clinical data allows monitoring of population trends in EOL care and identifies high-risk populations for future interventions.

Susceptibility Factors to Ozone-Related Mortality-A Population-Based Case-Crossover Analysis

Epidemiology ◽  
2009 ◽  
Vol 20 ◽  
pp. S26-S27 ◽  
Author(s):  
Massimo Stafoggia ◽  
Annunziata Faustini ◽  
Giovanna Berti ◽  
Gabriele Accetta ◽  
Luigi Bisanti ◽  
...  
Keyword(s):  
Population Based ◽  
Case Crossover ◽  
Susceptibility Factors ◽  
Crossover Analysis ◽  
Related Mortality
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