[Epidemiological signatures and surveillance bias in cancer]. / Signatures épidémiologiques et biais de surveillance du cancer.

Surveillance bias occurs when variations in cancer incidence are the result of changes in screening or diagnostic practices rather than increases in the true occurrence of cancer. This bias is linked to the issue of overdiagnosis and can be apprehended by looking at epidemiological signatures of cancer. We explain the concept of epidemiological signatures using the examples of melanoma and of lung and prostate cancer. Accounting for surveillance bias is particularly important for assessing the true burden of cancer and for accurately communicating cancer information to the population and decision-makers.

Le biais de surveillance se produit lorsque les variations d'incidence d'un cancer sont le résultat d'un changement dans les pratiques de dépistage ou de diagnostic plutôt que d'une augmentation de la fréquence réelle de ce cancer. Ce biais est lié au concept du surdiagnostic et peut être appréhendé en examinant les signatures épidémiologiques des cancers. Nous expliquons le concept de signature épidémiologique à l'aide des exemples du mélanome et des cancers du poumon et de la prostate. La prise en compte des biais de surveillance est particulièrement importante pour évaluer le fardeau réel du cancer et communiquer avec précision l'information sur le cancer à la population et aux décideurs.

Impact of annual trend volume of low-dose computed tomography for lung cancer screening on overdiagnosis, overmanagement, and gender disparities.

BACKGROUND: With the increasing prevalence of nonsmoking-related lung cancer in Asia, Asian countries have increasingly adopted low-dose computed tomography (LDCT) for lung cancer screening, particularly in private screening programs. This study examined how annual LDCT volume affects lung cancer stage distribution, overdiagnosis, and gender disparities using a hospital-based lung cancer database. METHODS: This study analyzed the annual utilized LDCT volume, clinical characteristics of lung cancer, stage shift distribution, and potential overdiagnosis. At the individual level, this study also investigated the relationship between stage 0 lung cancer (potential strict definition regarding overdiagnosis) and the clinical characteristics of lung cancer. RESULTS: This study reviewed the annual trend of 4971 confirmed lung cancer cases from 2008 to 2021 and conducted a link analysis with an LDCT imaging examination database over these years. As the volume of lung cancer screenings has increased over the years, the number and proportion of stage 0 lung cancers have increased proportionally. Our study revealed that the incidence of stage 0 lung cancer increased with increasing LDCT scan volume, particularly during the peak growth period from 2017 to 2020. Conversely, stage 4 lung cancer cases remained consistent across different time intervals. Furthermore, the increase in the lung cancer screening volume had a more pronounced effect on the increase in stage 0 lung cancer cases among females than it had among males. The estimated potential for overdiagnosis brought about by the screening process, compared to non-participating individuals, ranged from an odds ratio of 7.617 to one of 17.114. Both strict and lenient definitions of overdiagnosis (evaluating cases of stage 0 lung cancer and stages 0 to 1 lung cancer) were employed. CONCLUSIONS: These results provide population-level evidence of potential lung cancer overdiagnosis in the Taiwanese population due to the growing use of LDCT screening, particularly concerning the strict definition of stage 0 lung cancer. The impact was greater in the female population than in the male population, especially among females younger than 40 years. To improve lung cancer screening in Asian populations, creating risk-based prediction models for smokers and nonsmokers, along with gender-specific strategies, is vital for ensuring survival benefits and minimizing overdiagnosis.

[The overdiagnosis of thyroid cancer should not be overinterpreted].

Recently, the topic of "overdiagnosis" of thyroid cancer has once again sparked controversy in the medical academic community, as well as extensive discussions from patients and the general population. To some extent, the overdiagnosis of thyroid cancer has been over interpreted. This article provides a detailed discussion on how to correctly understand the overdiagnosis of thyroid cancer from the perspective of a thyroid surgeon. The author believes that there are two elements to the occurrence of overdiagnosis of thyroid cancer: the presence of a large "silent pool" of inert tumors in the human body and medical methods to improve detection rates. In recent years, thyroid cancer has become the fastest growing malignant tumor in the world in terms of incidence rate. The exponential growth mode makes thyroid cancer over diagnosed and inevitably becomes a hot topic in academia. However, the overdiagnosis of thyroid cancer is not contradictory to the early screening and diagnosis of thyroid cancer. The overdiagnosis of thyroid cancer should be viewed scientifically and rationally, especially avoiding overinterpretation.

[Controversy and boundary in the diagnose and treatment of thyroid cancer].

In recent years, the incidence of thyroid cancer has rapidly increased, whereas the mortality rate has not risen correspondingly. Therefore, scholars at home and abroad have proposed the view of overdiagnosis in thyroid cancer, sparking intense debates about the phenomenon of overdiagnosis and overtreatment. A historical review and discussion of the primary reasons for the increase in thyroid cancer incidence and the improvement in treatment outcomes are beneficial. It helps clarify that the real increase in thyroid cancer is primarily due to the higher incidence rate, rather than overdiagnosis. Additionally, it allows us to reevaluate which factors guarantee favorable efficacy in thyroid cancer.

Contents analysis of thyroid cancer-related information uploaded to YouTube by physicians in Korea: endorsing thyroid cancer screening, potentially leading to overdiagnosis.

BACKGROUND: Thyroid cancer overdiagnosis is a major public health issue in South Korea, which has the highest incidence rate. The accessibility of information through the Internet, particularly on YouTube, could potentially impact excessive screening. This study aimed to analyze the content of thyroid cancer-related YouTube videos, particularly those from 2016 onwards, to evaluate the potential spread of misinformation. METHODS: A total of 326 videos for analysis were collected using a video search protocol with the keyword "thyroid cancer" on YouTube. This study classified the selected YouTube videos as either provided by medical professionals or not and used topic clustering with LDA (latent dirichlet allocation), sentiment analysis with KoBERT (Korean bidirectional encoder representations from transformers), and reliability evaluation to analyze the content. The proportion of mentions of poor prognosis for thyroid cancer and the categorization of advertising content was also analyzed. RESULTS: Videos by medical professionals were categorized into 7 topics, with "Thyroid cancer is not a 'Good cancer'" being the most common. The number of videos opposing excessive thyroid cancer screening decreased gradually yearly. Videos advocating screening received more favorable comments from viewers than videos opposing excessive thyroid cancer screening. Patient experience videos were categorized into 6 topics, with the "Treatment process and after-treatment" being the most common. CONCLUSION: This study found that a significant proportion of videos uploaded by medical professionals on thyroid cancer endorse the practice, potentially leading to excessive treatments. The study highlights the need for medical professionals to provide high-quality and unbiased information on social media platforms to prevent the spread of medical misinformation and the need for criteria to judge the content and quality of online health information.

The over diagnosis of diffuse mesothelioma: An analysis of 311 cases with recommendations for the avoidance of pitfalls.

BACKGROUND: The diagnosis of mesothelioma may be challenging. We investigated a large database of cases in order to determine the frequency with which a diagnosis of mesothelioma was made incorrectly and the most frequent causes of error. DESIGN: A database including more than 4000 consultation cases of histologically confirmed mesothelioma was examined to identify cases in which mesothelioma was diagnosed by at least one pathologist when the available information pointed towards a different diagnosis. RESULTS: There were 311 cases misdiagnosed as mesothelioma. The most common category was metastatic carcinoma to the pleura or peritoneum (129 cases: 73 lung carcinomas, 15 renal cell carcinomas). The next most common category was primary lung cancer (111 cases: 55 sarcomatoid carcinoma, 56 pseudomesotheliomatous carcinoma). The third most common category was primary malignancies arising from or near the serosal membranes (33 cases). The fourth most common category was fibrous pleurisy (38 cases). The most common errors were failure to consider important radiographic information regarding the gross distribution of tumor, lack of awareness or consideration of another malignancy, overreliance on certain immunohistochemical results, and failure to perform certain diagnostic histochemical, immunohistochemical, or ultrastructural studies. CONCLUSIONS: There are a number of diagnostic pitfalls that can lead to the over diagnosis of mesothelioma. Careful attention to clinical and radiographic information as well as performance of appropriate ancillary tests can help to prevent such misdiagnoses. Detailed examples will be presented to assist in the avoidance of these pitfalls with emphasis on the most commonly observed errors.

Ecological study estimating melanoma overdiagnosis in the USA using the lifetime risk method.

OBJECTIVES: To quantify the proportion of melanoma diagnoses (invasive and in situ) in the USA that might be overdiagnosed. DESIGN: In this ecological study, incidence and mortality data were collected from the Surveillance, Epidemiology and End Results 9 registries database. DevCan software was used to calculate the cumulative lifetime risk of being diagnosed with melanoma between 1975 and 2018, with adjustments made for changes in longevity and risk factors over the study period. SETTING: USA. PARTICIPANTS: White American men and women (1975-2018). MAIN OUTCOME MEASURES: The primary outcome was excess lifetime risk of melanoma diagnosis between 1976 and 2018 (adjusted for year 2018 competing mortality and changes in risk factors), which was inferred as likely overdiagnosis. The secondary outcome was an excess lifetime risk of melanoma diagnosis in each year between 1976 and 2018 (adjusted and unadjusted). RESULTS: Between 1975 and 2018 the adjusted lifetime risk of being diagnosed with melanoma (invasive and in situ) increased from 3.2% (1 in 31) to 6.4% (1 in 16) among white men, and from 1.6% (1 in 63) to 4.5% (1 in 22) among white women. Over the same period, the adjusted lifetime risk of being diagnosed with melanoma in situ increased from 0.17% (1 in 588) to 2.7% (1 in 37) in white men and 0.08% (1 in 1250) to 2.0% (1 in 50) in white women. An estimated 49.7% of melanomas diagnosed in white men and 64.6% in white women were overdiagnosed in 2018. Among people diagnosed with melanomas in situ, 89.4% of white men and 85.4% of white women were likely overdiagnosed in 2018. CONCLUSIONS: Melanoma overdiagnosis among white Americans is significant and increasing over time with an estimated 44 000 overdiagnosed in men and 39 000 in women in 2018. A large proportion of overdiagnosed melanomas are in situ cancers, pointing to a potential focus for intervention.

Overdiagnosis in malignant melanoma: a scoping review.

OBJECTIVES: We aimed to systematically identify and scrutinise published empirical evidence about overdiagnosis in malignant melanoma and examine how frequent overdiagnosis of melanoma is and whether this is related to different types of interventions or diagnostic technologies. DESIGN AND SETTING: Empirical studies that discussed overdiagnosis in malignant melanoma were eligible, including qualitative and quantitative studies in any type of population, age group and geographical location. We excluded studies that did not include empirical data, studies that only mentioned 'overdiagnosis' without addressing it further and studies that used the term overdiagnosis for cases of misdiagnosis or false positives.We developed the search strategy in cooperation with an information specialist. We searched five databases on 21 April 2022: MEDLINE, Embase, CINAHL, PsycINFO and Cochrane Library.This scoping review adheres to The JBI methodology and Prefered Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping reviews (PRISMA-ScR). Two reviewers independently screened titles, abstracts and full texts for inclusion and extracted data from the included studies. The data extracted include study characteristics, population details, research question, the context and the study's main results. RESULTS: Our search resulted in 1134 potentially relevant studies. 35 studies were included: 29 register studies, 3 cohort studies, 1 case-control study, 1 survey study and 1 randomised controlled trial. Most register studies examined trends in melanoma incidence and/or mortality and found a significant increase in incidence between 0.39% and 6.6% annually and a little or no increase in mortality. Three cohort studies and one case-control study showed that skin screening was associated with increased detection of melanoma; especially in situ or thin invasive melanoma. Three studies estimated the degree of overdiagnosis which ranged from 29% to 60%. CONCLUSIONS: Epidemiological data suggest a high degree of overdiagnosis in malignant melanoma. Studies that examined the association between skin screening and malignant melanoma all found increased detection of melanomas, mostly thin and in situ melanomas, which raises concern about overdiagnosis.

Cancer Screening, Incidental Detection, and Overdiagnosis.

BACKGROUND: In the past, patients were only diagnosed with cancer because they had symptoms. Now, because of screening and incidental detection, some patients are diagnosed with cancer when they are asymptomatic. While this shift is typically viewed as desirable, it has produced an unfortunate side-effect: it is now possible to be diagnosed with a cancer not destined to cause symptoms or death-a phenomenon labeled as overdiagnosis. CONTENT: We begin with a brief introduction to the heterogeneity of cancer progression: at one extreme, some cancers are already systemic by the time they are detectable; at the other, some grow extremely slowly or even regress. The ensuing sections describe the evidence that the pursuit of earlier detection has led to overdiagnosis. Although rarely confirmed in an individual, overdiagnosis is readily identifiable in a long-term follow-up of a randomized trial of screening. Furthermore, 2 population signatures for overdiagnosis exist: (a) rising incidence coupled with stable mortality and (b) rising early-stage incidence coupled with stable late-stage incidence. Finally, we review the misleading feedback produced by overdiagnosis-such as rising 5-year survival rates and more cancer survivors. This feedback is erroneously interpreted as reinforcing the value of early detection, encourages more screening/incidental detection and, ironically, promotes more overdiagnosis. SUMMARY: Overdiagnosis is an unintended consequence of the desire to detect cancer early. Given the evolving understanding that tumor biology and host response are more relevant to prognosis than early vs late diagnosis, it is time to challenge the assertion that early diagnosis is always the best approach to curing cancer.

A novel image deep learning-based sub-centimeter pulmonary nodule management algorithm to expedite resection of the malignant and avoid over-diagnosis of the benign.

OBJECTIVES: With the popularization of chest computed tomography (CT) screening, there are more sub-centimeter (≤ 1 cm) pulmonary nodules (SCPNs) requiring further diagnostic workup. This area represents an important opportunity to optimize the SCPN management algorithm avoiding "one-size fits all" approach. One critical problem is how to learn the discriminative multi-view characteristics and the unique context of each SCPN. METHODS: Here, we propose a multi-view coupled self-attention module (MVCS) to capture the global spatial context of the CT image through modeling the association order of space and dimension. Compared with existing self-attention methods, MVCS uses less memory consumption and computational complexity, unearths dimension correlations that previous methods have not found, and is easy to integrate with other frameworks. RESULTS: In total, a public dataset LUNA16 from LIDC-IDRI, 1319 SCPNs from 1069 patients presenting to a major referral center, and 160 SCPNs from 137 patients from three other major centers were analyzed to pre-train, train, and validate the model. Experimental results showed that performance outperforms the state-of-the-art models in terms of accuracy and stability and is comparable to that of human experts in classifying precancerous lesions and invasive adenocarcinoma. We also provide a fusion MVCS network (MVCSN) by combining the CT image with the clinical characteristics and radiographic features of patients. CONCLUSION: This tool may ultimately aid in expediting resection of the malignant SCPNs and avoid over-diagnosis of the benign ones, resulting in improved management outcomes. CLINICAL RELEVANCE STATEMENT: In the diagnosis of sub-centimeter lung adenocarcinoma, fusion MVCSN can help doctors improve work efficiency and guide their treatment decisions to a certain extent. KEY POINTS: • Advances in computed tomography (CT) not only increase the number of nodules detected, but also the nodules that are identified are smaller, such as sub-centimeter pulmonary nodules (SCPNs). • We propose a multi-view coupled self-attention module (MVCS), which could model spatial and dimensional correlations sequentially for learning global spatial contexts, which is better than other attention mechanisms. • MVCS uses fewer huge memory consumption and computational complexity than the existing self-attention methods when dealing with 3D medical image data. Additionally, it reaches promising accuracy for SCPNs' malignancy evaluation and has lower training cost than other models.

Factors associated with overdiagnosis of benign pulmonary nodules as malignancy: a retrospective cohort study.

OBJECTIVE: To establish a preoperative model for the differential diagnosis of benign and malignant pulmonary nodules (PNs), and to evaluate the related factors of overdiagnosis of benign PNs at the time of imaging assessments. MATERIALS AND METHODS: In this retrospective study, 357 patients (median age, 52 years; interquartile range, 46-59 years) with 407 PNs were included, who underwent surgical histopathologic evaluation between January 2020 and December 2020. Patients were divided into a training set (n = 285) and a validation set (n = 122) to develop a preoperative model to identify benign PNs. CT scan features were reviewed by two chest radiologists, and imaging findings were categorized. The overdiagnosis rate of benign PNs was calculated, and bivariate and multivariable logistic regression analyses were used to evaluate factors associated with benign PNs that were over-diagnosed as malignant PNs. RESULTS: The preoperative model identified features such as the absence of part-solid and non-solid nodules, absence of spiculation, absence of vascular convergence, larger lesion size, and CYFRA21-1 positivity as features for identifying benign PNs on imaging, with a high area under the receiver operating characteristic curve of 0.88 in the validation set. The overdiagnosis rate of benign PNs was found to be 50%. Independent risk factors for overdiagnosis included diagnosis as non-solid nodules, pleural retraction, vascular convergence, and larger lesion size at imaging. CONCLUSION: We developed a preoperative model for identifying benign and malignant PNs and evaluating factors that led to the overdiagnosis of benign PNs. This preoperative model and result may help clinicians and imaging physicians reduce unnecessary surgery.