AIM: Length time bias is a selection bias which can lead to an overestimation of survival of screening-detected cases caused by the relative excess of slower-growing tumors detected with respect to symptomatic cases. This leads to the incorrect perception that screening improves outcomes when it only selects tumors with a favorable biology. Data regarding this bias in surveillance for hepatocellular carcinoma (HCC) have never been provided. METHODS: A semi-Markov model was developed to investigate this issue. An exponential tumor growth was applied. During its growth, tumor diagnosis "at surveillance appointments" was made when tumor attained a size equal to or above the size of tumors diagnosed in surveilled patients obtained from pertinent published reports, or "in-between appointments" (due to the development of symptoms) if tumor size attained the size of symptomatic diagnosis, derived from published reports; otherwise the tumor continued to grow until the time horizon had been reached. Tumor doubling time (DT) values were recorded according to the method of diagnosis. RESULTS: In a theoretical cohort of 1000 patients submitted to semiannual surveillance, 72.5% will be diagnosed at a surveillance appointment and 18% because of symptom development, although under surveillance. Patients diagnosed with HCC at a surveillance appointment had a median tumor DT of 100 days (interquartile range, 68-143 days), whereas those diagnosed because of symptoms had a median DT of 42 days (interquartile range, 29-58 days) although under surveillance. CONCLUSION: The surveillance propensity to detect slower-growth tumors is relevant, and practical suggestions to minimize this bias in longitudinal studies are provided.
AIM: Length time bias is a selection bias which can lead to an overestimation of survival of screening-detected cases caused by the relative excess of slower-growing tumors detected with respect to symptomatic cases. This leads to the incorrect perception that screening improves outcomes when it only selects tumors with a favorable biology. Data regarding this bias in surveillance for hepatocellular carcinoma (HCC) have never been provided. METHODS: A semi-Markov model was developed to investigate this issue. An exponential tumor growth was applied. During its growth, tumor diagnosis "at surveillance appointments" was made when tumor attained a size equal to or above the size of tumors diagnosed in surveilled patients obtained from pertinent published reports, or "in-between appointments" (due to the development of symptoms) if tumor size attained the size of symptomatic diagnosis, derived from published reports; otherwise the tumor continued to grow until the time horizon had been reached. Tumor doubling time (DT) values were recorded according to the method of diagnosis. RESULTS: In a theoretical cohort of 1000 patients submitted to semiannual surveillance, 72.5% will be diagnosed at a surveillance appointment and 18% because of symptom development, although under surveillance. Patients diagnosed with HCC at a surveillance appointment had a median tumor DT of 100 days (interquartile range, 68-143 days), whereas those diagnosed because of symptoms had a median DT of 42 days (interquartile range, 29-58 days) although under surveillance. CONCLUSION: The surveillance propensity to detect slower-growth tumors is relevant, and practical suggestions to minimize this bias in longitudinal studies are provided.