KIM-1 as a blood-based marker for early detection of kidney cancer: a prospective nested case-control study
Authors: Ghislaine Scelo, David C. Muller, Elio Riboli, Mattias Johannson, Amanada J. Cross, Paolo Vineis, Konstantinos K. Tsilidis, Paul Brennan, Heiner Boeing, Petra HM Peters, Roel Vermeulen, Kim Overvad, Bas Bueno-de-Mesquita, Gianluca Severi, Vittorio Perduca, Marina Kvaskoff, Antonia Trichopoulou, Carlo La Vecchia, Anna Karakatsani, Domenico Palli, Sabina Sieri, Salvatore Panico, Elisabete Weiderpass, Torkjel M Sandanger, Therese H. Nøst, Antonio Agudo, J. Ramón Quirós, Miguel Rodríguez-Barranco, Maria-Dolores Chirlaque, Timothy J Key, Prateek Khanna, Joseph V. Bonventre, Venkata S Sabbisetti, Rupal S. Bhatt
Summary:
Purpose: Renal cell carcinoma (RCC) has the potential for cure with surgery when diagnosed at an early stage. Kidney injury molecule-1 (KIM-1) has been shown to be elevated in the plasma of RCC patients. We aimed to test whether plasma KIM-1 could represent a means of detecting RCC prior to clinical diagnosis.
Experimental Design: KIM-1 concentrations were measured in pre-diagnostic plasma from 190 RCC cases and 190 controls nested within a population-based prospective cohort study. Cases had entered the cohort up to five years before diagnosis, and controls were matched on cases for date of birth, date at blood donation, sex, and country. We applied conditional logistic regression and flexible parametric survival models to evaluate the association between plasma KIM-1 concentrations and RCC risk and survival.
Results: The incidence rate ratio (IRR) of RCC for a doubling in KIM-1 concentration was 1.71 (95% confidence interval [CI]: 1.44-2.03, p-value = 4.1x10-23), corresponding to an IRR of 63.3 (95% CI: 16.2-246.9) comparing the 80th to the 20th percentile of the KIM-1 distribution in this sample. Compared with a risk model including known risk factors of RCC (age, sex, country, body mass index and tobacco smoking status), a risk model additionally including KIM-1 substantially improved discrimination between cases and controls (area under the receiver operating characteristic curve of 0.8 compared to 0.7). High plasma KIM-1 concentrations were also associated with poorer survival (p=0.0053).
Conclusions: Plasma KIM-1 concentrations could predict RCC incidence up to 5 years prior to diagnosis and were associated with poorer survival.
Source: Clinical Cancer Research, 2018; clincanres.1496.2018
Summary:
Purpose: Renal cell carcinoma (RCC) has the potential for cure with surgery when diagnosed at an early stage. Kidney injury molecule-1 (KIM-1) has been shown to be elevated in the plasma of RCC patients. We aimed to test whether plasma KIM-1 could represent a means of detecting RCC prior to clinical diagnosis.
Experimental Design: KIM-1 concentrations were measured in pre-diagnostic plasma from 190 RCC cases and 190 controls nested within a population-based prospective cohort study. Cases had entered the cohort up to five years before diagnosis, and controls were matched on cases for date of birth, date at blood donation, sex, and country. We applied conditional logistic regression and flexible parametric survival models to evaluate the association between plasma KIM-1 concentrations and RCC risk and survival.
Results: The incidence rate ratio (IRR) of RCC for a doubling in KIM-1 concentration was 1.71 (95% confidence interval [CI]: 1.44-2.03, p-value = 4.1x10-23), corresponding to an IRR of 63.3 (95% CI: 16.2-246.9) comparing the 80th to the 20th percentile of the KIM-1 distribution in this sample. Compared with a risk model including known risk factors of RCC (age, sex, country, body mass index and tobacco smoking status), a risk model additionally including KIM-1 substantially improved discrimination between cases and controls (area under the receiver operating characteristic curve of 0.8 compared to 0.7). High plasma KIM-1 concentrations were also associated with poorer survival (p=0.0053).
Conclusions: Plasma KIM-1 concentrations could predict RCC incidence up to 5 years prior to diagnosis and were associated with poorer survival.
Source: Clinical Cancer Research, 2018; clincanres.1496.2018