Trends in kidney cancer among the elderly in Denmark, 1980–2012

Azawi, Nessn; Joergensen, Simon Moeller; Jensen, Niels Viggo; Clark, Peter E.; Lund, Lars

doi:10.3109/0284186x.2015.1115121

Cited by 16 publications

(18 citation statements)

References 13 publications

(14 reference statements)

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“…Fixed multivariable regression models were used to estimate clinical outcomes according to each concomitant medication category following adjustment for preplanned adjusting covariates that might represent confounders. [22][23][24] The key covariates were: primary tumor type (NSCLC, melanoma, renal cell carcinoma and others), age (<70 vs ≥70 years), [25][26][27][28] sex (male vs female), Eastern Cooperative Oncology Group-Performance Status (ECOG-PS) (0-1 vs ≥2), burden of disease (number of metastatic sites≤2 vs >2), treatment line (first vs non-first) and BMI. BMI was used given to its alleged role in affecting immunotherapy clinical outcomes 15 16 and as a surrogate of cardiovascular/ metabolic conditions which might have influenced the prescription of certain concomitant medications.…”

Section: Materials and Methods Study Designmentioning

confidence: 99%

Integrated analysis of concomitant medications and oncological outcomes from PD-1/PD-L1 checkpoint inhibitors in clinical practice

Cortellini

Tucci

Adamo

et al. 2020

J Immunother Cancer

161

170

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BackgroundConcomitant medications, such as steroids, proton pump inhibitors (PPI) and antibiotics, might affect clinical outcomes with immune checkpoint inhibitors.MethodsWe conducted a multicenter observational retrospective study aimed at evaluating the impact of concomitant medications on clinical outcomes, by weighing their associations with baseline clinical characteristics (including performance status, burden of disease and body mass index) and the underlying causes for their prescription. This analysis included consecutive stage IV patients with cancer, who underwent treatment with single agent antiprogrammed death-1/programmed death ligand-1 (PD-1/PD-L1) with standard doses and schedules at the medical oncology departments of 20 Italian institutions. Each medication taken at the immunotherapy initiation was screened and collected into key categories as follows: corticosteroids, antibiotics, gastric acid suppressants (including proton pump inhibitors - PPIs), statins and other lipid-lowering agents, aspirin, anticoagulants, non-steroidal anti-inflammatory drugs (NSAIDs), ACE inhibitors/Angiotensin II receptor blockers, calcium antagonists, β-blockers, metformin and other oral antidiabetics, opioids.ResultsFrom June 2014 to March 2020, 1012 patients were included in the analysis. Primary tumors were: non-small cell lung cancer (52.2%), melanoma (26%), renal cell carcinoma (18.3%) and others (3.6%). Baseline statins (HR 1.60 (95% CI 1.14 to 2.25), p=0.0064), aspirin (HR 1.47 (95% CI 1.04 to 2.08, p=0.0267) and β-blockers (HR 1.76 (95% CI 1.16 to 2.69), p=0.0080) were confirmed to be independently related to an increased objective response rate. Patients receiving cancer-related steroids (HR 1.72 (95% CI 1.43 to 2.07), p<0.0001), prophylactic systemic antibiotics (HR 1.85 (95% CI 1.23 to 2.78), p=0.0030), prophylactic gastric acid suppressants (HR 1.29 (95% CI 1.09 to 1.53), p=0.0021), PPIs (HR 1.26 (95% CI 1.07 to 1.48), p=0.0050), anticoagulants (HR 1.43 (95% CI: 1.16 to 1.77), p=0.0007) and opioids (HR 1.71 (95% CI 1.28 to 2.28), p=0.0002) were confirmed to have a significantly higher risk of disease progression. Patients receiving cancer-related steroids (HR 2.16 (95% CI 1.76 to 2.65), p<0.0001), prophylactic systemic antibiotics (HR 1.93 (95% CI 1.25 to 2.98), p=0.0030), prophylactic gastric acid suppressants (HR 1.29 (95% CI 1.06 to 1.57), p=0.0091), PPI (HR 1.26 (95% CI 1.04 to 1.52), p=0.0172), anticoagulants (HR 1.45 (95% CI 1.14 to 1.84), p=0.0024) and opioids (HR 1.53 (95% CI 1.11 to 2.11), p=0.0098) were confirmed to have a significantly higher risk of death.ConclusionWe confirmed the association between baseline steroids administered for cancer-related indication, systemic antibiotics, PPIs and worse clinical outcomes with PD-1/PD-L1 checkpoint inhibitors, which can be assumed to have immune-modulating detrimental effects.

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Section: Materials and Methods Study Designmentioning

confidence: 99%

Integrated analysis of concomitant medications and oncological outcomes from PD-1/PD-L1 checkpoint inhibitors in clinical practice

Cortellini

Tucci

Adamo

et al. 2020

J Immunother Cancer

161

170

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“…The following clinical factors were evaluated: BMI (obese, overweight, normal weight, underweight), primary tumor (NSCLC, melanoma, kidney and others), age (<70 vs ≥70 years old) [19][20][21][22] , sex (male vs female), Eastern Cooperative Oncology Group Performance Status (ECOG-PS) (0-1 vs ≥2), burden of disease (number of metastatic sites ≤2 vs >2) and treatment line (first vs non-first). In order to properly weighing the impact on clinical outcomes and to find appropriate covariates, the correlations between SMI and SMD (according the study cut offs) and baseline clinical factors (primary tumor, age, ECOG-PS, burden of disease and treatment line) were evaluated with the chi-square test.…”

Section: Methodsmentioning

confidence: 99%

Weighing the role of skeletal muscle mass and muscle density in cancer patients receiving PD-1/PD-L1 checkpoint inhibitors: a multicenter real-life study

Cortellini

Bozzetti

Palumbo

et al. 2020

Sci Rep

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Sarcopenia represents one of the hallmarks of all chronic diseases, including cancer, and was already investigated as a prognostic marker in the pre-immunotherapy era. Sarcopenia can be evaluated using cross-sectional image analysis of CT-scans, at the level of the third lumbar vertebra (L3), to estimate the skeletal muscle index (SMI), a surrogate of skeletal muscle mass, and to evaluate the skeletal muscle density (SMD). We performed a retrospective analysis of consecutive advanced cancer patient treated with PD-1/PD-L1 checkpoint inhibitors. Baseline SMI and SMD were evaluated and optimal cut-offs for survival, according to sex and BMI (+/−25) were computed. The evaluated clinical outcomes were: objective response rate (ORR), immune-related adverse events (irAEs), progression free survival (PFS) and overall survival (OS). From April 2015 to April 2019, 100 consecutive advanced cancer patients were evaluated. 50 (50%) patients had a baseline low SMI, while 51 (51%) had a baseline low SMD according to the established cut offs. We found a significant association between SMI and ECOG-PS (p = 0.0324), while no correlations were found regarding SMD and baseline clinical factors. The median follow-up was 20.3 months. Patients with low SMI had a significantly shorter PFS (HR = 1.66 [95% CI: 1.05-2.61]; p = 0.0291) at univariate analysis, but not at the multivariate analysis. They also had a significantly shorter OS (HR = 2.19 [95% CI: 1.31-3.64]; p = 0.0026). The multivariate analysis confirmed baseline SMI as an independent predictor for OS (HR = 2.19 [1.31-3.67]; p = 0.0027). We did not find significant relationships between baseline SMD and clinical outcomes, nor between ORR, irAEs and baseline SMI (data not shown). Low SMI is associated with shortened survival in advanced cancer patients treated with PD1/PDL1 checkpoint inhibitors. However, the lack of an association between SMI and clinical response suggests that sarcopenia may be generally prognostic in this setting rather than specifically predictive of response to immunotherapy.Sarcopenia is the condition of loss of muscle mass, with decreased muscle power, and it is one of the hallmarks of cancer, which negatively affects the most of clinical outcomes such as toxicities and survival 1 . The interactions must recognize also the lack of other adiposity metrics, such as the waist circumference, the waist-to-height ratio, and the body fat percentage. Moreover, the CT imaging analysis was limited by the data availability; indeed, the acquisition protocol was planned according to the presence of previous examination. conclusionOur finding of a significant shorter OS for low-SMI patients treated with PD-1/PD-L1 checkpoint inhibitors, suggests that sarcopenia might have a prognostic role, rather than predictive. However, to properly weighing our results, we must consider the significant association between poorer PS and low-SMI. Without making conclusive considerations, we can assume that after the advent of ICIs, we should give back further relevance to baseline nut...

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“…Data from NORDCAN showed that the proportion of patients diagnosed with kidney cancer over the age of 70 years has decreased from 43% in 1980 to 32% in 2012 in men and remained almost constant in women, around 50%. Incidence rates were at least five times higher in men aged 70 years or more but there was no particular trend with time (Azawi et al 2016). In men aged less than 70 years, the incidence rates started increasing around 2000.…”

Section: Kidney Cancermentioning

confidence: 84%

“…More patients with metastatic kidney cancer are now being offered systemic treatments with metastatic disease. A recommendation of dose modification for elderly patients with metastatic kidney cancer is needed (Azawi et al 2016) and TKI or mTOR treatments should be offered to elderly patients on the same terms as younger patients. The study concludes that when managing kidney cancer in the elderly it is essential to establish interdisciplinary collaborations between different specialties, such as surgeons, clinical oncologists, and geriatricians, to be able to deliver the best possible care in the future.…”

Section: Kidney Cancermentioning

confidence: 99%

Population Trends in Aging and Cancer

Lund

2017

Geriatric Oncology

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Several recent studies from Denmark have shown that age is the strongest risk factor for developing cancer. These reports gave an overview of the trends in cancer incidence, mortality, prevalence, and relative survival in Denmark from 1980 to 2012 focusing on age, comparing persons aged 70 years or more with those aged less than 70 years. Data was collected from the NORDCAN database with comparable data on cancer incidence, mortality, prevalence, and relative survival in the Nordic countries. The Danish data originate from the Danish Cancer Registry and the Danish Cause of Death Registry with follow-up for death or emigration until the end of 2013. The studies found a higher incidence and mortality rates of all sites, but nonmelanoma skin cancer, and that the relative survival was lower among persons aged 70 years or more than those aged less than 70 years. The age distribution remained constant over time while the percentage of persons dying from cancer decreased with time up to the age of 79 years but increased for those aged 80 years or more, in whom about a third of all cancer deaths occurred in 2012. There was an increase in the number of prevalent cancer

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Trends in kidney cancer among the elderly in Denmark, 1980–2012

Abstract: A challenge in managing kidney cancer in the elderly is to establish interdisciplinary collaborations between different specialties, such as surgeons, clinical oncologists, and geriatricians to be able to deliver the best possible care in the future.

Cited by 16 publications

References 13 publications

Integrated analysis of concomitant medications and oncological outcomes from PD-1/PD-L1 checkpoint inhibitors in clinical practice

Integrated analysis of concomitant medications and oncological outcomes from PD-1/PD-L1 checkpoint inhibitors in clinical practice

Weighing the role of skeletal muscle mass and muscle density in cancer patients receiving PD-1/PD-L1 checkpoint inhibitors: a multicenter real-life study

Population Trends in Aging and Cancer

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