Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): Explanation and Elaboration

The REMARK “elaboration and explanation” guideline, by Doug Altman and colleagues, provides a detailed reference for authors on important issues to consider when designing, conducting, and analyzing tumor marker prognostic studies

Prognostic and Predictive Markers in Cancer

The elucidation of the human genome and advances in knowledge about molecular abnormalities, signaling pathways, influence of the local tissue milieu and the relevance of genetic polymorphisms offer hope of designing more effective, individualized cancer treatment plans. Although the scientific and medical literature is replete with reports of putative prognostic or predictive markers for cancer, few new diagnostics have been incorporated into routine clinical practice. Criteria are needed to a) identify markers that have the promise to be clinically useful; b) assess the best methodology for clinical evaluation of the markers in question and c) confirm or validate that using the marker adds useful information compared to using standard prognostic factors alone. This review presents a methodology for the clinical evaluation of putative prognostic and predictive markers in cancer, with considerations of pitfalls in the early evaluation, rationale for development and optimization of assay methodology, and examples of possible clinical trials for assessing the clinical utility of putative markers

A Perspective On Challenges And Issues In Biomarker Development And Drug And Biomarker Codevelopment

A workshop sponsored by the National Cancer Institute and the US Food and Drug Administration addressed past lessons learned and ongoing challenges faced in biomarker development and drug and biomarker codevelopment. Participants agreed that critical decision points in the product life cycle depend on the level of understanding of the biology of the target and its interaction with the drug, the preanalytical and analytical factors affecting biomarker assay performance, and the clinical disease process. The more known about the biology and the greater the strength of association between an analytical signal and clinical result, the more efficient and less risky the development process will be. Rapid entry into clinical practice will only be achieved by using a rigorous scientific approach, including careful specimen collection and standardized and quality-controlled data collection. Early interaction with appropriate regulatory bodies will ensure studies are appropriately designed and biomarker test performance is well characterized

Kaplan-Meier plot for disease-free survival comparing patients with HU177 concentrations above and below the median value.

<p> <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001216#pmed.1001216-Hamilton1" target="_blank">[178]</a></p

Multivariable Cox regression analysis of relapse-free survival in patients with primary breast cancer showing the impact of adding the marker (PMN-E) to a base model of recognized prognostic variables [59].

a<p>Age in decades for pre- and postmenopausal patients;</p>b<p>Positive, ≥10 fmol/mg protein; negative <10 ng/mg protein;</p>c<p>High, >36.4 ng/mg protein; low, ≤36.4 ng/mg protein;</p>d<p>Log-transformed variable.</p><p>CI: confidence interval; ER: estrogen receptor; PgR: progesterone receptor.</p

Example of the REMARK profile illustrated using data from a study of ploidy in patients with advanced ovarian cancer [157] (from [20]).

a<p>Not considered for survival outcome as these factors are not considered as ‘standard’ factors and/or number of missing values was relatively large;</p>b<p>values not given in the paper.</p

Relation between marker (serum chromogranin A) and patient characteristics [181] (note that missing data were not indicated).

<p>CgA: chromogranin A; ECOG PS: Eastern Cooperative Oncology Group performance status; NSCLC: non-small cell lung cancer; Q1 to Q3: interquartile range.</p

Relation between patient characteristics and steroid receptor status by immunocytochemistry and dextran-coated charcoal [159].

a<p>No information available on tumor size in 12 cases;</p>b<p>mucinous, tubular or medullary;</p>c<p>no information available on tumor grade in 24 cases.</p><p>DCC: dextran-coated charcoal; ICC: immunocytochemistry.</p