scholarly journals Stage at diagnosis for children with blood cancers in Australia: Application of the Toronto Paediatric Cancer Stage Guidelines in a population‐based national childhood cancer registry

2019 ◽  
Vol 66 (6) ◽  
pp. e27683 ◽  
Author(s):  
Danny R. Youlden ◽  
Sumit Gupta ◽  
A. Lindsay Frazier ◽  
Andrew S. Moore ◽  
Peter D. Baade ◽  
...  
2015 ◽  
Vol 25 (6) ◽  
pp. 966-972 ◽  
Author(s):  
Pegdwende O. Dialla ◽  
Patrick Arveux ◽  
Samiratou Ouedraogo ◽  
Carole Pornet ◽  
Aurélie Bertaut ◽  
...  

2018 ◽  
Vol 201 ◽  
pp. 62-69 ◽  
Author(s):  
A. Toender ◽  
T. Munk-Olsen ◽  
M. Vestergaard ◽  
J.T. Larsen ◽  
N.P. Suppli ◽  
...  

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 1522-1522
Author(s):  
Laura-Maria Madanat-Harjuoja ◽  
Janne Pitkäniemi ◽  
Elli Hirvonen ◽  
Nea Malila ◽  
Lisa Diller

1522 Background: Population based data on risk of cancer in relatives of childhood cancer patients are sparse. Using linked population-based registries, we set out to evaluate risk of early onset cancer in first-degree relatives of childhood cancer patients. Methods: We queried the Finnish Cancer Registry and ascertained a cohort of 9135 individuals diagnosed with at least one cancer under the age of 21 years between 1970 and 2012. We then went on to identify a total of 58,211 unique first- and second-degree relatives by linking to the Central Population Registry. Relatives were then linked back to the annually updated Finnish Cancer Registry to identify cancer diagnoses in siblings, offspring and parents of childhood cancer patients, restricting to cancers occurring under the age of 40. Risk of cancer in relatives of the index case was estimated using standardized incidence ratios (SIRs) comparing cancer age and period specific incidence in relatives to that of the general population. Results: A total of 288 cancers were diagnosed in relatives during the 900,907 years of follow-up, while 266 cancers were expected. The overall risk of cancer in siblings of childhood cancer patients was elevated (SIR 1.18 95% CI 1.00-1.39). 144 of the childhood cancer patients were identified as having a sibling additional to index case with a diagnosis of cancer at age < 40; 44 of these 144 also had a parent with early onset cancer. The risk of early onset cancer was elevated in offspring overall (SIR 1.79 95%CI 1.05-2.81) and in offspring of retinoblastoma, malignant bone tumor and neuroblastoma patients. Siblings of lymphoma patients were at elevated risk of early cancer, and the mothers of 11 of 27 sibling pairs (lymphoma + cancer < 40 yo) also had cancer at age < 40. Conclusions: Linked registries allow family history of cancer to be evaluated across multiple relatives and to be longitudinally updated. Results are generally reassuring with regard to risk of cancer in relatives of childhood cancer patients. Elevated risk in relatives of retinoblastoma and malignant bone tumor patients are in line with the known cancer syndromes associated with these tumor types, and lymphoma and neuroblastoma families need further analysis.


2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 67s-67s
Author(s):  
R. Long ◽  
A. Woods ◽  
C. Biondi ◽  
J. Luzuriaga ◽  
C. Anderiesz ◽  
...  

Background: Stage at diagnosis is an important prognostic factor for cancer, providing contextual information for interpreting population health indicators such as mortality from cancer and cancer survival. Australian population-based cancer registries (PBCRs) routinely collect information on cancer incidence and mortality. The need for high quality, comprehensive national data on stage at diagnosis to supplement these data are widely recognized in Australia. The collection and dissemination of quality national stage data will enhance the: • ability to better monitor cancer outcomes, inform cancer control policy; • understand variations across different populations; and • identify where further research and targeted strategies may be required to improve cancer outcomes. Linking data on cancer stage at diagnosis with other administrative cancer data will also allow for a better understanding of the relationship between stage at diagnosis, treatments received, patterns of cancer recurrence, and survival outcomes. Aim: To strengthen national data capacity by collecting and reporting cancer stage at diagnosis for Cancer Australia's Stage, Treatment and Recurrence (STaR) project. Methods: Working with state and territory population-based cancer registries (PBCRs) and the Australian Pediatric Cancer Registry, Cancer Australia supported the development and testing of Business Rules for the collection of national cancer stage at diagnosis for: • The top 5 incident cancers based on the Tumor, Node, and Metastasis (TNM) staging system. These rules were endorsed by the Australasian Association of Cancer Registries (AACR) as a national standard in May 2016; and • Childhood cancers, with a separate set of Business Rules for 16 childhood cancer types based on the Toronto Pediatric Cancer Stage Guidelines. These rules were supported by the AACR as a national standard. Results: Using the AACR-endorsed Business Rules, comprehensive national cancer stage at diagnosis data for the top 5 incident cancers (for 2011) have been collected in Australia for the first time. Over 90% of incidence cases were able to be assigned a value for registry-derived (RD) stage at diagnosis for melanoma (97%), prostate (97%), and female breast (94%) cancers. Lower staging completeness was found for colorectal cancers (88%), and for lung cancers (72%). Business Rules for the collection of stage at diagnosis data for pediatric cancers have also been developed; 93% of sample cases diagnosed in the period 2006-2010 were able to be staged, ranging from 84% for nonrhabdomyosarcoma to 100% for hepatoblastoma. Conclusion: The Business Rules enabled the uniform collection of cancer stage at diagnosis data for the first time in Australia. The collection of these data will allow for the linkage of stage at diagnosis to other sources of information, including patterns of treatments applied, and enable reporting of survival and recurrence outcomes by stage.


2020 ◽  
Vol 67 (6) ◽  
Author(s):  
Carlotta Sacerdote ◽  
Maria Luisa Mosso ◽  
Daniela Alessi ◽  
Franco Merletti ◽  
Giovanna Tagliabue ◽  
...  

2018 ◽  
Vol 2 (3) ◽  
pp. 173-179 ◽  
Author(s):  
Joanne F Aitken ◽  
Danny R Youlden ◽  
Andrew S Moore ◽  
Peter D Baade ◽  
Leisa J Ward ◽  
...  

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1572-1572
Author(s):  
Siran M. Koroukian ◽  
Jennifer Tsui ◽  
Weichuan Dong ◽  
Xiaoyu Yan ◽  
Uriel Kim ◽  
...  

1572 Background: Studies to date have shown post-Medicaid expansion (M-exp) decreases in the percentage of cancer patients who are uninsured and improvements in cancer stage at diagnosis in states that expanded Medicaid as part of the Affordable Care Act. However, most studies have examined impact of M-exp on stage outcomes at the population level, or among Medicaid and uninsured, rather than solely in the Medicaid population. Using cancer registry data from a non M-exp state (Georgia (GA)) and two M-exp states (Ohio (OH) and New Jersey (NJ)), we compared changes in cancer stage in patients on Medicaid, accounting for individual- and contextual-level characteristics at the Zip Code Tabulation Area (ZCTA) level. Methods: We used GA, OH, and NJ cancer registry data for individuals 20-64 years of age and diagnosed with incident invasive female breast (BC), cervical (CC), and colorectal cancer (CRC). Data spanned from 2010-2017 for GA and OH, and from 2011-2016 for NJ (for BC and CRC only), with 2014 marking the year in which Medicaid was expanded in OH and NJ. We retrieved demographic data (age, race/ethnicity, sex for CRC, insurance status, and cancer stage from the cancer registries), and obtained ZCTA-level data from the American Community Survey (e.g., income, education, and female-headed households). We defined late-stage diagnosis as regional- or distant- stage. We conducted multivariable logistic regression models by state and cancer site to examine changes in late-stage cancer diagnosis pre- and post-M-exp, accounting for individual- and ZCTA-level covariates. Results: The number of patients with incident cancer who were on Medicaid increased by 41.7% (n = 1757 to 2490), 59.6% (327 to 522), and 76.4% (953 to 1681) for BC, CC, and CRC cancers, respectively, in Ohio; by 92.4% (433 to 833) for BC and by over 100% for CRC (232 to 496) in NJ; but by 12.7% (662 to 746) among CRC patients in GA, where the number of BC and CC patients on Medicaid remained relatively stable. Adjusting for individual and contextual-level factors, the adjusted risk ratio (ARR and (95% Confidence Interval)) for late-stage disease was lowest for BC patients in OH (0.93 (0.87, 0.99)) and for CRC patients in GA (0.94 (0.89, 0.99)). The ARR for BC and CRC in NJ were not statistically significant, though they trended towards improvement. Similarly, changes in late-stage for CC were not statistically significant in OH or in GA. Conclusions: The increased number of cancer patients in Medicaid and the reductions in late-stage diagnosis observed may potentially translate into reduced, or at least stabilized, cancer-related morbidity and mortality burden among Medicaid beneficiaries over time. However, reductions in late-stage diagnosis were not consistent across cancer sites or states, possibly due to differences in population demographics, health behaviors, healthcare seeking patterns, and state-level cancer prevention efforts.


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