Characteristics and Survival Outcomes of Second Primary Cancers in Long-term Retinoblastoma Survivors.

PURPOSE: Retinoblastoma (RB) is the most common intraocular cancer and is associated with lifelong risks of developing a second primary cancer, especially in patients with hereditary RB and/or childhood exposure to radiotherapy. METHODS: The study included all consecutive patients with a history of RB treated for a second primary cancer during 1994-2018. Patient demographics and characteristics of the primary RB and second primary cancer were examined. The associations among radiation or chemotherapy exposure as a treatment for RB, unilateral versus bilateral status, types and multiplicity of second primary cancers, and survival after diagnosis of second primary cancer were analyzed. RESULTS: A wide spectrum of second primary cancer types was identified from 62 eligible patients (30 males and 32 females), including sarcoma, breast cancer, various skin cancers, gastrointestinal and genitourinary cancers, and endocrine cancers. Of all patients who had second primary cancers, 40 patients (65%) had bilateral RB and 17 patients (27%) had unilateral RB. Thirty-five patients (56%) who developed second primary cancers received radiation therapy during childhood as the treatment of RB, and 17 patients (27%) received chemotherapy for the treatment of RB. The 5-year and 10-year survival rates for RB patients diagnosed with a second primary cancer were 54.0% and 36.0%, respectively. The median age of onset of second primary cancer among RB survivors was 36.6 years. CONCLUSIONS: In contrast to previous studies, we found a broader spectrum of second primary cancer types. All RB survivors, regardless of unilateral or bilateral status, should undergo strict cancer surveillance particularly as they approach the fourth decade of life.

Age Associated Coronavirus Disease 2019 Incubation Period: Impact on Quarantine Policy

Knowledge of the incubation period of coronavirus disease 2019 (COVID-19), defined as the time from infection to symptom onset, is critical to effectively confine COVID-19. However, the incubation period of COVID-19 is not always observed exactly due to uncertain onsets of infection and disease symptom. In this paper, we demonstrate how to estimate the distribution of incubation and its association with patient demographic factors when the dates of infection and disease onset are not explicitly. We employ a sufficiently general parametric class, the generalized odds-rate class of regression models, which includes the log-logistic proportional odds model and the Weibull proportional hazards model as special cases. We base our analysis on publicly reported, clinically confirmed COVID-19 cases with potential exposure period information. The application indicates that an age-specific quarantine policy might be more efficient than a unified one in confining COVID-19.