CONDITIONAL SURVIVAL IN ONCOLOGY: A REVIEW.
Abstract
OBJECTIVES:
To conduct a review of conditional survival (CS) in urologic oncology, in addition to examining CS in other leading cancer primaries. CS provides dynamic information on a patient’s probability of survival by accounting for disease free interval (DFI), which invariably improves survival probability relative to immediate estimates at diagnosis or treatment.
METHODS:
A review of the literature was performed using PubMed, Medline, and Cochrane databases focusing on all articles addressing CS. Electronic articles published ahead of print were also considered. Search was limited to the English language and relied on keywords: conditional survival, oncology, urological oncology, and cancer. Studies were selected according to sample size, contemporaneity, and clinical relevance of the results.
RESULTS:
CS estimates are available for six urological cancers: (1) renal cell carcinoma, (2) squamous cell carcinoma of the penis, (3) urothelial cancer of urinary bladder, (4) upper tract urothelial carcinoma, (5) prostate cancer and (6) testicular cancer. Furthermore, CS estimates are available for three leading cancer primaries: (1) breast cancer, (2) colorectal cancer and (3) lung cancer. These estimates have been devised based on population data, as well as institutional databases. External validation and accuracy were reported for two CS models predicting cancer specific mortality in renal cell carcinoma and penile carcinoma.
CONCLUSIONS:
CS improves the precision of predictions, among patients who enjoy a disease-free survival (DFS), by accounting for disease free survival time. It is a dynamic measure that results in better prognosis in proportion to the length of DFS. Despite its advantage over survival probabilities without adjustment for DFI, CS is not incorporated in most prognostic models.
Keywords
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DOI: http://dx.doi.org/10.18103/imr.v3i1.287
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