Browsing by Author "Nevala, Aapeli"
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Ekholm, Mauritz; Nevala, Aapeli; Malila, Nea; Virtanen, Anni (2023)Objectives Few studies have focused on the association between childhood and young adulthood cancers and cancer screening attendance. Our aim was to assess the effect of cancer diagnosed before the age of 30 years on first-time cervical screening attendance. Methods Using the nation-wide and population-based Finnish Cancer Registry and the Mass Screening Registry, we identified 4,491 cancer patients born between years 1961 and 1988 and diagnosed with cancer before age 30 and alive at the time of first cervical cancer screening invitation at age 25 or 30 years. Attendance probability to screening was compared between individuals with and without a prior cancer diagnosis. Results Compared to women with no previous cancer (attendance probability of 58% in study period), difference in attendance to first-time screening invitation was observed among women with previous cervical cancer (24%), other malignant gynaecologic cancer (43%) and borderline ovarian tumours (48%). Attendance among women with other previous cancer types did not differ from women with no previous cancer. Differences in the attendance probability of cancer survivors and cancer free individuals also varied between catchment areas. Conclusions The low cervical cancer screening attendance among survivors of previous gynecologic cancers and borderline ovarian tumors calls for further exploration on the reasons. As attendance probability differed among survivors of gynecological and other types of cancer significantly only if the invitation came <5 years after the cancer diagnosis, one likely explanation is ongoing oncologic follow-up. Regional differences underline the importance of national guidelines.
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Nevala, Aapeli (2020)Thanks to modern medical advances, humans have developed tools for detecting diseases so early, that a patient would be better off had the disease gone undetected. This is called overdiagnosis. Overdiagnosisisaproblemespeciallycommoninacts,wherethetargetpopulationofanintervention consists of mostly healthy people. Colorectal cancer (CRC) is a relatively rare disease. Thus screening for CRC affects mostly cancerfree population. In this thesis I evaluate overdiagnosis in guaiac faecal occult blood test (gFOBT) based CRC screening programme. In gFOBT CRC screening there are two goals: to detect known predecessors of cancers called adenomas and to remove them (cancer prevention), and to detect malign CRCs early enough to be still treatable (early detection). Overdiagnosis can happen when detecting adenomas, but also when detecting cancers. This thesis focuses on overdiagnosis due to detection of adenomas that are non-progressive in their nature. Since there is no clinical means to make distinction between progressive and non-progressive adenomas, statistical methods must be applied. Classical methods to estimate overdiagnosis fail in quantifying this type of overdiagnosis for couple of reasons: incidence data of adenomas is not available, and adenoma removal results in lowering cancer incidence in screened population. While the latter is a desired effect of screening, it makes it impossible to estimate overdiagnosis by just comparing cancer incidences among screened and control populations. In this thesis a Bayesian Hidden Markov model using HMC NUTS algorithm via software Stan is fitted to simulate the natural progression of colorectal cancer. The five states included in the model were healthy (1), progressive adenoma (2), screen-detectable CRC (3), clinically apparent CRC (4) and non-progressive adenoma (5). Possible transitions are from 1 to 2, 1 to 5, 2 to 3 and 3 to 4. The possible observations are screen-negative (1), detected adenoma (2), screen-detected CRC (3), clinically manifested CRC (3). Three relevant estimands for evaluating this type of overdiagnosis with a natural history model are presented. Then the methods are applied to estimate overdiagnosis proportion in guaiac faecal occult blood test (gFOBT) based CRC screening programme conducted in Finland between 2004 and 2016. The resulting mean overdiagnosis probability for all the patients that had an adenoma detected for programme is 0.48 (0.38, 0.56, 95-percent credible interval). Different estimates for overdiagnosis in sex and age-specific stratas of the screened population are also provided. In addition to these findings, the natural history model can be used to gain more insight about natural progression of colorectal cancer.
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