The Biomarker Toolkit - an evidence-based guideline to predict cancer biomarker success and guide development

Abstract

Background: An increased number of resources are allocated on cancer biomarker discovery, but very few of these biomarkers are clinically adopted. To bridge the gap between Biomarker discovery and clinical use, we aim to generate the Biomarker Toolkit, a tool designed to identify clinically promising biomarkers and promote successful biomarker translation.

Methods: All features associated with a clinically useful biomarker were identified using mixed-methodology, including systematic literature search, semi-structured interviews, and an online two-stage Delphi-Survey. Validation of the checklist was achieved by independent systematic literature searches using keywords/subheadings related to clinically and non-clinically utilised breast and colorectal cancer biomarkers. Composite aggregated scores were generated for each selected publication based on the presence/absence of an attribute listed in the Biomarker Toolkit checklist.

Results: Systematic literature search identified 129 attributes associated with a clinically useful biomarker. These were grouped in four main categories including: rationale, clinical utility, analytical validity, and clinical validity. This checklist was subsequently developed using semi-structured interviews with biomarker experts (n=34); and 88.23% agreement was achieved regarding the identified attributes, via the Delphi survey (consensus level:75%, n=51). Quantitative validation was completed using clinically and non-clinically implemented breast and colorectal cancer biomarkers. Cox-regression analysis suggested that total score is a significant driver of biomarker success in both cancer types (BC: p>0.0001, 95.0% CI: 0.869-0.935, CRC: p>0.0001, 95.0% CI: 0.918-0.954).

Conclusions: This novel study generated a validated checklist with literature-reported attributes linked with successful biomarker implementation. Ultimately, the application of this toolkit can be used to detect biomarkers with the highest clinical potential and shape how biomarker studies are designed/performed.

Keywords: Biomarkers; Breast cancer; Clinical utility; Colorectal cancer; Translational research.

Fig. 1

Scores and impact factor of successful and stalled breast and colorectal cancer BM publications. A) Bar chart indicating the total average scores between successful. (n=105) and stalled Biomarkers (n=80). B) Bar chart showing the individual average scores in CV, AV and CU categories. C) Bar chart indicating the total average scores between successful (n=132) and stalled CRC Biomarkers (n=123). D) Bar chart showing the individual average scores in CV, AV and CU categories. Asterisks denote the level of significance where ns: P > 0.05 *: P≤ 0.05, **: P ≤0.01, ***: P ≤0.001, ****: P ≤0.0001. All of the evaluated publications were independently scored by two assessors (BC: 50% of the journals by SM and 50% by MS; CRC 50% IP and 50% MK) as a validation of toolkit scoring strategy, with less than 12% difference between original and reviewer 1 and 2 scores, suggesting low inter-rater variability. AV, analytical validity; CV, clinical utility; CU, clinical utility; BM, biomarkers; CRC, colorectal cancer; BC, breast cancer

Fig. 2

Successful and stalled biomarker clinical utility studies. Stacked bar chart showing AV, analytical validity; CE, cost-effectiveness; CUs, clinical usefulness; FEAS, feasibility; HF, human factor; IMPL, implementation; and DA, decisional analysis studies in successful A) BC, B) CRC biomarkers and stalled C) BC and D) CRC biomarkers. BC, breast cancer, CRC, colorectal cancer

Fig. 3

Performance outcomes in successful and stalled breast and CRC biomarkers studies: scatter plot showing PPV, positive predictive value; NPV, negative predictive value; Spec., specificity; Sens, sensitivity; AUROC, area under the curve in A) BC and B) CRC successful (open circles) and stalled (closed circles) biomarkers. BC, breast cancer, CRC, colorectal cancer