Grant Details
Grant Number: |
5R01CA262375-03 Interpret this number |
Primary Investigator: |
Kang, Stella |
Organization: |
New York University School Of Medicine |
Project Title: |
Tailored Screening for Urinary System Cancers in Patients with Chronic Kidney Disease |
Fiscal Year: |
2024 |
Abstract
Project Summary
Chronic kidney disease (CKD) is a highly prevalent condition, found in 20% of people aged 50 years and
older. While it is well known that CKD is strongly associated with cardiovascular mortality, recent work has
demonstrated an association with cancer risk that also merits consideration for preventive strategies. Cancer is
the leading cause of death in mid-life patients afflicted by early stages of CKD, and the 2nd leading cause
across all CKD patients under 65 years. Specifically, kidney cancers occur three times more often in patients
with CKD, including a hazard ratio of up to 3.4 in younger men (40-52 years) with moderate CKD (15-60
mL/min/1.73 m2). Indeed, the incidence of kidney cancer in mid-life patients with CKD is similar to that of
colorectal cancer in the general population. Risks of bladder cancer are similarly increased in CKD. Current
guidelines recommend that CKD patients undergo monitoring of common renal and cardiovascular risk factors
that overlap with those of urinary tract cancers such as smoking, hypertension, and obesity. Thus, the lack of
clear cancer screening recommendations represents an important gap in CKD practice guidelines, and may be
due to the complex weighing of benefits and harms for a population with wide-ranging health status.
Our team of experts in decision science, epidemiology, urologic oncology, nephrology, radiology, and
internal medicine will apply complementary experience to assess the potential of screening strategies. We
previously developed and published a computer simulation model of kidney tumors and comorbidities,
supported by an NCI K award, the Renal Anatomy and Function for Renal Masses (Re-AFFiRM) simulation
model. Our model is capable of simulating outcomes of subpopulations defined by CKD severity and kidney
tumor natural history. We will transform the model to incorporate bladder cancer natural history as well as
kidney and bladder screening pathways. We will assess whether cancer screening pathways benefit life
expectancy and quality-adjusted life expectancy based on age, CKD stage, strong co-existing risk factors, and
comorbidity burden. Middle-aged adults without other significant cardiovascular comorbidity and multiple
established risk factors may warrant more intensive screening, whereas patients with cardiovascular disease
and few risk factors may warrant less intensive screening. In addition, Black men and women with CKD have
been shown repeatedly to suffer higher all-cause and cancer-specific mortality compared to non-Black CKD
patients, an important consideration in forming screening recommendations. Our findings will be evaluated by
a group of independent stakeholders in primary care, nephrology, urology, and patient advocacy to consider
the acceptability and barriers to screening as supported by the model results. Cost-effectiveness will also be
explored for key factors that affect or elevate the value of screening. Our goal will be to establish the context in
which urinary tract screening recommendations could benefit the large population with CKD.
Publications
Chronic kidney disease and risk of kidney or urothelial malignancy: systematic review and meta-analysis.
Authors: Brooks E.R.
, Siriruchatanon M.
, Prabhu V.
, Charytan D.M.
, Huang W.C.
, Chen Y.
, Kang S.K.
.
Source: Nephrology, Dialysis, Transplantation : Official Publication Of The European Dialysis And Transplant Association - European Renal Association, 2024-05-31 00:00:00.0; 39(6), p. 1023-1033.
PMID: 38037426
Related Citations
How to Perform Economic Evaluation in Implementation Studies: Imaging-Specific Considerations and Comparison of Financial Models.
Authors: Kang S.K.
, Gold H.T.
.
Source: Journal Of The American College Of Radiology : Jacr, 2023 Mar; 20(3), p. 292-298.
PMID: 36922103
Related Citations