The diagnostic performance of current tumour markers in surveillance for recurrent testicular cancer: A diagnostic test accuracy systematic review
Nicholson BD., Jones NR., Protheroe A., Joseph J., Roberts NW., Van den Bruel A., Fanshawe TR.
In this diagnostic test accuracy systematic review we summarise the evidence on the diagnostic accuracy of blood α-fetoprotein (AFP), human chorionic gonadotropin (HCG) and lactate dehydrogenase (LDH) in surveillance for testicular cancer recurrence in adults. We searched four electronic databases for studies that reported the diagnostic accuracy of HCG, AFP, and/or LDH in sufficient detail for sensitivity and specificity to be calculated by extracting a 2 × 2 table comparing biomarker positivity with testicular cancer recurrence. Screening, data extraction and QUADAS-2 quality assessment were completed by two independent reviewers. From 2406 studies, nine met our inclusion criteria. Eight reported data at the per-patient level. Sample sizes were small (range 5 to 449 patients) and clinical heterogeneity precluded meta-analysis. In most studies the specificity for recurrence with AFP and HCG was high (90–100%) but sensitivity was often relatively low, suggesting that many recurrences would not be detected by tumour markers alone. The diagnostic performance of LDH appears poorer. Studies were methodologically weak, with probable selection, incorporation and partial verification bias, and many studies were excluded for not reporting on recurrence-free patients. Limitations including small sample sizes, high heterogeneity, and inconsistent and incomplete reporting mean these results must be interpreted with caution. Despite inclusion of biomarkers in international surveillance guidance, there remains a lack of high quality evidence about their accuracy, optimal thresholds, and the most effective surveillance strategy in relation to contemporary investigative modalities. Higher quality research using data from modern-day follow-up cohorts is necessary to identify opportunities to reduce unnecessary testing.