Prediction of cancer incidence in Tyrol/Austria for year of diagnosis 2020

Oberaigner, Willi; Geiger-Gritsch, S.

doi:10.1007/s00508-014-0596-3

Cited by 8 publications

(4 citation statements)

References 22 publications

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“…This age-related distribution reflects the general distribution of malignancies according to current cancer statistics [38,39]. In contrast, no malignant disease was detected in patients younger than 30 years.…”

Section: Discussionsupporting

confidence: 62%

Malignant disease as an incidental finding at 18F-FDG-PET/CT scanning in patients with granulomatous lung disease

Huber¹,

Hodolič²,

Stelzmüller³

et al. 2015

Nuclear Medicine Communications

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Differentiation between granulomatous inflammation and malignancy is challenging with ¹⁸F-FDG-PET/CT because of a large number of false-positive findings. The highest probability of detecting coexistent malignant disease was seen in patients older than 60 years who were suffering from tuberculosis. An important feature for identification of malignant disease, especially in the assessment of intrathoracic findings, has turned out to be the CT pattern; quantitative evaluation, in contrast, seems to have little clinical value.

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Section: Discussionsupporting

confidence: 62%

Malignant disease as an incidental finding at 18F-FDG-PET/CT scanning in patients with granulomatous lung disease

Huber¹,

Hodolič²,

Stelzmüller³

et al. 2015

Nuclear Medicine Communications

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“…We are also confronted with an aging population. Due to a growing number of cancer survivors this becomes an increasing health concern also in Austria [ 39 ], as these patients may impact the overall quality of long-term care in this growing population, like elsewhere [ 40 ].…”

Section: Discussionmentioning

confidence: 99%

The relative risk of second primary cancers in Austria’s western states: a retrospective cohort study

Preyer¹,

Concin

Obermair

et al. 2017

BMC Cancer

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BackgroundCancer survivors are at risk of developing a second primary cancer (SPC) later in life because of persisting effects of genetic and behavioural risk factors, the long-term sequelae of chemotherapy, radiotherapy and the passage of time. This is the first study with Austrian data on an array of entities, estimating the risk of SPCs in a population-based study by calculating standardized incidence ratios (SIRs).MethodsThis retrospective cohort study included all invasive incident cancer cases diagnosed within the years 1988 to 2005 being registered in the Tyrol and Vorarlberg Cancer Registries. Person years at risk (PYAR) were calculated from time of first diagnosis plus 2 months until the exit date, defined as the date of diagnosis of the SPC, date of death, or end of 2010, whichever came first. SIR for specific SPCs was calculated based on the risk of these patients for this specific cancer.ResultsA total of 59,638 patients were diagnosed with cancer between 1988 and 2005 and 4949 SPCs were observed in 399,535 person-years of follow-up (median 5.7 years). Overall, neither males (SIR 0.90; 95% CI 0.86–0.93) nor females (SIR 1.00; 95% CI 0.96–1.05) had a significantly increased SIR of developing a SPC. The SIR for SPC decreased with age showing a SIR of 1.24 (95% CI 1.12–1.35) in the age group of 15–49 and a SIR of 0.85 (95% CI 0.82–0.89) in the age group of ≥ 65. If the site of the first primary cancer was head/neck/larynx cancer in males and females (SIR 1.88, 95% CI 1.67–2.11 and 1.74, 95% CI 1.30–2.28), cervix cancer in females (SIR 1.40, 95% CI 1.14–1.70), bladder cancer in males (SIR 1.20, 95% CI 1.07–1.34), kidney cancer in males and females (SIR 1.22, 95% 1.04–1.42 and 1.29, 95% CI 1.03–1.59), thyroid gland cancer in females (SIR 1.40, 95% CI 1.11–1.75), patients showed elevated SIR, developing a SPC.ConclusionsSurvivors of head & neck, bladder/kidney, thyroid cancer and younger patients show elevated SIRs, developing a SPC. This has possible implications for surveillance strategies.Electronic supplementary materialThe online version of this article (10.1186/s12885-017-3683-9) contains supplementary material, which is available to authorized users.

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“…Eighty-eight studies used projection methods not incorporating data on smoking,1 2 9 17–101 16 studies used a method incorporating data on smoking,3 7 33 41 42 102–112 and 6 studies used multiple methods 18 33 36 41 42 62. Overall, APC models were the most commonly used method to project lung cancer rates (44 studies used this method),2 9 17–58 and other GLMs were the next most commonly used (35 studies) 18 36 59–89 100 101. Only 12 studies used the present state method by assuming that the average cancer rates in the most recent years will remain constant into the future 1 62 90–99.…”

Section: Resultsmentioning

confidence: 99%

Statistical projection methods for lung cancer incidence and mortality: a systematic review

Luo

Hughes

et al. 2019

BMJ Open

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ObjectivesTo identify and summarise all studies using statistical methods to project lung cancer incidence or mortality rates more than 5 years into the future.Study typeSystematic review.MethodsWe performed a systematic literature search in multiple electronic databases to identify studies published from 1 January 1988 to 14 August 2018, which used statistical methods to project lung cancer incidence and/or mortality rates. Reference lists of relevant articles were checked for additional potentially relevant articles. We developed an organisational framework to classify methods into groups according to the type of data and the statistical models used. Included studies were critically appraised using prespecified criteria.ResultsOne hundred and one studies met the inclusion criteria; six studies used more than one statistical method. The number of studies reporting statistical projections for lung cancer increased substantially over time. Eighty-eight studies used projection methods, which did not incorporate data on smoking in the population, and 16 studies used a method which did incorporate data on smoking. Age–period–cohort models (44 studies) were the most commonly used methods, followed by other generalised linear models (35 studies). The majority of models were developed using observed rates for more than 10 years and used data that were considered to be good quality. A quarter of studies provided comparisons of fitted and observed rates. While validation by withholding the most recent observed data from the model and then comparing the projected and observed rates for the most recent period provides important information on the model’s performance, only 12 studies reported doing this.ConclusionThis systematic review provides an up-to-date summary of the statistical methods used in published lung cancer incidence or mortality projections. The assessment of the strengths of existing methods will help researchers to better apply and develop statistical methods for projecting lung cancer rates. Some of the common methods described in this review can be applied to the projection of rates for other cancer types or other non-infectious diseases.

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Prediction of cancer incidence in Tyrol/Austria for year of diagnosis 2020

Cited by 8 publications

References 22 publications

Malignant disease as an incidental finding at 18F-FDG-PET/CT scanning in patients with granulomatous lung disease

Malignant disease as an incidental finding at 18F-FDG-PET/CT scanning in patients with granulomatous lung disease

The relative risk of second primary cancers in Austria’s western states: a retrospective cohort study

Statistical projection methods for lung cancer incidence and mortality: a systematic review

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