Prognostic significance of PI-RADS 5 lesions in patients treated by radical prostatectomy.

PURPOSE: To analyse the pathological features and survival of patients with a PI-RADS 5 lesion on pre-biopsy MRI. METHODS: We extracted from a European multicentre prospectively gathered database the data of patients with a PI-RADS 5 lesion on pre-biopsy MRI, diagnosed using both systematic and targeted biopsies and subsequently treated by radical prostatectomy. The Kaplan-Meier model was used to assess the biochemical-free survival of the whole cohort and univariable and multivariable Cox models were set up to study factors associated with survival. RESULTS: Between 2013 and 2019, 539 consecutive patients with a PI-RADS 5 lesion on pre-biopsy MRI were treated by radical prostatectomy and included in the analysis. Follow-up data were available for 448 patients. Radical prostatectomy and lymph node dissection specimens showed non-organ confined disease in 297/539 (55%), (including 2 patients with a locally staged pT2 lesion and lymph node involvement (LNI)). With a median follow-up of 25 months (12-39), the median biochemical recurrence-free survival was 54% at 2 years (95% CI 45-61) and 28% at 5 years (95% CI 18-39). Among the factors studied, MRI T stage [T3a vs T2 HR 3.57 (95%CI 1.78-7.16); T3b vs T2 HR 6.17 (95% CI 2.99-12.72)] and PSA density (HR 4.47 95% CI 1.55-12.89) were significantly associated with a higher risk of biochemical recurrence in multivariable analysis. CONCLUSION: Patients with a PI-RADS 5 lesion on pre-biopsy MRI have a high risk of early biochemical recurrence after radical prostatectomy. MRI T stage and PSA density can be used to improve patient selection and counselling.

[Interval between two smear tests for cervical cancer screening and characteristics of women with a short interval: Study in the department of Isère]. / Délai entre deux frottis de dépistage du cancer du col utérin et caractéristiques des femmes présentant un délai court : étude dans le département de l'Isère.

AIMS: In France, guidelines for cervical cancer screening recommend that women between the ages of 25-65 have a smear test performed once every three years. However, some women are screened significantly more frequently. In this study, we used a data-driven approach as opposed to a traditional hypothesis-driven approach to characterise the population of women who are screened more frequently than advised. METHODS: Data came from an organised cervical cancer screening programme of a French department in the Alps (Isère). We retrospectively selected women aged between 25 to 65 years old who had at least two smear tests during the follow up period (2011-2015). We used a data-driven clustering approach to compare the population of over-screened women with other populations. We then performed a descriptive analysis of the over-screened population using univariate (Chi2 test) and multivariate (logistic regression) methods. RESULTS: A total of 10,000 patients were randomly chosen from a population of 54,073. In our univariate analysis, women in the over-screened population were significantly younger, participated less in organised screening, were more likely to be followed by a gynaecologist and had more smear test results showing inflammation than the other populations. Patient location (urban v.s. rural area) was not significant for this population. The multivariate analysis confirmed these results. CONCLUSION: This data-driven approach based on an unsupervised learning method enables us to more accurately characterise the over-screened population. These data invite to improve communication with the youngest women and the gynecologists to recall the benefit of an interval between two normal smears complying with the recommendations. This approach could help to improve the prevention and have a real impact on this Public Health issue.

Are comorbidities associated with long-term survival of lung cancer? A population-based cohort study from French cancer registries.

BACKGROUND: Survival rates of lung cancer remains poor and the impact of comorbidities on the prognosis is discussed. The objective of this study was to assess if the Charlson Comorbidity Index (CCI) was associated with 8-year survival rates by histological type. METHODS: A cohort study was conducted using randomly selected cases from 10 French cancer registries. Net survival rates were computed using the Pohar-Perme estimator of the net cumulative rate. Three Cox models were independently built for adenocarcinomas, squamous cell and small cell cancers to estimate prognostic factors including CCI grade. RESULTS: A total of 646 adenocarcinomas, 524 squamous cell and 233 small cell cancers were included in the analysis. The net 8-year survival rate ranged from 12.6% (95% CI: 9.8-15.4%) for adenocarcinomas and 13.4% (95% CI: 10.1-16.7%) for squamous cell carcinomas, to 3.7% (95% CI: 1.1-6.3%) for small cell cancers. Observed and net survival rates decreased for CCI grades ≥3 for all histological group considered. After adjustment for sex, age group, stage and diagnostic mode, CCI grades 1 (HR = 1.6 [95% CI: 1.1-2.3]), 2 (HR = 1.7 [95% CI: 1.1-2.7]) and ≥ 3 (HR = 2.7 [95% CI: 1.7-4.4]) were associated with lower survival rates only for small cell cancers. CONCLUSION: After adjustment for age, sex, stage and diagnostic mode, the presence of comorbidity based on CCI grades 1-2 and ≥ 3 was associated with lower survival rates for small cell cancers whereas no differences were observed for adenocarcinomas and squamous cell cancers.

Overdiagnosis associated with breast cancer screening: A simulation study to compare lead-time adjustment methods.

OBJECTIVE: Estimating overdiagnosis associated with breast cancer screening may use annual incidence rates of cancer. We simulated populations invited to screening programmes to assess two lead-time adjustment methods. METHODS: Overdiagnosis estimates were computed using the compensatory drop method, which considered the decrease in incidence of cancers among older age groups no longer offered screening, and the method based on the decrease in incidence of late-stage cancers. RESULTS: The true value of overdiagnosis was 0% in all the data sets simulated. The compensatory drop method yielded an overdiagnosis estimate of -0.1% (95% credibility interval -0.5% to 0.5%) when participation rates among the population and risk of cancers were constant. However, if participation rates increased with calendar year as well as risk of cancer with birth cohorts, the overdiagnosis estimated was 11.0% (10.5-11.6%). Using the method based on the incidence of early- and late-stage cancers, overdiagnosis estimates were 8.9% (8.5-9.3%) and 17.6% (17.4-17.9%) when participation rates and risks of cancer were constant or increased with time, respectively. CONCLUSION: Adjustment for lead time based on the compensatory drop method is accurate only when participation rates and risks of cancer remain constant, whereas the adjustment method based on the incidence of early- and late-stage cancers results in overestimating overdiagnosis regardless of stability of participation rates and breast cancer risk.

Do prostate cancer risk models improve the predictive accuracy of PSA screening? A meta-analysis.

BACKGROUND: Despite the extensive development of risk prediction models to aid patient decision-making on prostate screening, it is unknown whether these models could improve predictive accuracy of PSA testing to detect prostate cancer (PCa). The objective of this study was to perform a systematic review to identify PCa risk models and to assess the model's performance to predict PCa by conducting a meta-analysis. DESIGN: A systematic literature search of Medline was conducted to identify PCa predictive risk models that used at least two variables, of which one of the variables was prostate-specific antigen (PSA) level. Model performance (discrimination and calibration) was assessed. Prediction models validated in ≥5 study populations and reported area under the curve (AUC) for prediction of any or clinically significant PCa were eligible for meta-analysis. Summary AUC and 95% CIs were calculated using a random-effects model. RESULTS: The systematic review identified 127 unique PCa prediction models; however, only six models met study criteria for meta-analysis for predicting any PCa: Prostataclass, Finne, Karakiewcz, Prostate Cancer Prevention Trial (PCPT), Chun, and the European Randomized Study of Screening for Prostate Cancer Risk Calculator 3 (ERSPC RC3). Summary AUC estimates show that PCPT does not differ from PSA testing (0.66) despite performing better in studies validating both PSA and PCPT. Predictive accuracy to discriminate PCa increases with Finne (AUC = 0.74), Karakiewcz (AUC = 0.74), Chun (AUC = 0.76) and ERSPC RC3 and Prostataclass have the highest discriminative value (AUC = 0.79), which is equivalent to doubling the sensitivity of PSA testing (44% versus 21%) without loss of specificity. The discriminative accuracy of PCPT to detect clinically significant PCa was AUC = 0.71. Calibration measures of the models were poorly reported. CONCLUSIONS: Risk prediction models improve the predictive accuracy of PSA testing to detect PCa. Future developments in the use of PCa risk models should evaluate its clinical effectiveness in practice.

Translation of research results to simple estimates of the likely effect of a lung cancer screening programme in the United Kingdom.

BACKGROUND: There is considerable interest in the possibility of provision of lung cancer screening services in many developed countries. There is, however, no consensus on the target population or optimal screening regimen. METHODS: In this paper, we demonstrate the use of published results on lung cancer screening and natural history parameters to estimate the likely effects of annual and biennial screening programmes in different risk populations, in terms of deaths prevented and of human costs, including screening episodes, further investigation rates and overdiagnosis. RESULTS: Annual screening with the UK Lung Screening Study eligibility criteria was estimated to result in 956 lung cancer deaths prevented and 457 overdiagnosed cancers from 330,000 screening episodes. Biennial screening would result in 802 lung cancer deaths prevented and 383 overdiagnosed cancers for 180,000 screening episodes. INTERPRETATION/CONCLUSION: The predictions suggest that the intervention effect could justify the human costs. The evidence base for low-dose CT screening for lung cancer pertains almost entirely to annual screening. The benefit of biennial screening is subject to additional uncertainty but the issue merits further empirical research.

A systematic review of the characteristics associated with recall rates, detection rates and positive predictive values of computed tomography screening for lung cancer.

BACKGROUND: Low-dose computed tomography (LDCT) screening has been shown to reduce mortality from lung cancer but at a substantial cost in diagnostic activity. The objective of this study was to investigate the characteristics of screening programmes associated with recall rates, detection rates and positive predictive values (PPVs). DESIGN: We conducted a systematic review of randomised trials and observational studies on LDCT screening for lung cancer. A meta-regression using random-effect logistic regressions was carried out to assess factors influencing recall rates for further investigation, cancer detection rates and PPVs of recall. RESULTS: We used data from 63 372 prevalent screens from 16 studies of LDCT screening for lung cancer and 79 302 incident screens from nine studies. In univariable analysis, the use of a cut-off size to define nodules warranting further investigation at prevalent screens reduced recall rates [odds ratio (OR) = 0.44, 95% confidence interval (CI) 0.24-0.82 and OR = 0.42, 95% CI 0.21-0.84 for cut-off sizes of 3-4 and 5-8 mm, respectively], without significant changes in detection rates and PPVs. The number of readers (1 or ≥2) was not associated with changes in recall rates, detection rates and PPVs at prevalent and incident screens. Using the volumetry software at incident screens significantly increased the PPV (OR = 5.02, 95% CI 1.65-15.28) as a result of a decrease in recall rates (OR = 0.25, 95% CI 0.12-0.51), without significant changes in detection rates. CONCLUSION: These results highlight the value of using a cut-off size for nodules warranting further investigation with lower recall rates at prevalent screens, whereas the volumetric assessment software at incident screens results in lower recall rates and higher PPVs. The presence of positron emission tomography in the work-up protocol might be associated with lower rates of surgical procedures for benign findings, although this hypothesis deserves further investigation.

Comparison of interval breast cancer rates for two-versus single-view screening mammography: a population-based study.

OBJECTIVE: To determine whether the implementation of two-view mammography was followed by a reduction in the rates of interval cancers. MATERIAL AND METHOD: We analyzed the data concerning women aged 50-69 who attended the breast cancer screening program between January 1, 1994 and December 31, 2006 in Isère, France. We performed Poisson regressions to estimate age-adjusted rate ratios of women being recalled, cancer detection, and interval cancer for two-view compared to single-view mammography. RESULTS: After adjusting for age, two-view mammography was associated with a higher risk of cancer detection (1.37 [95% CI, 1.16-1.62]) and with a decreased risk of 12-month (0.46 [95% CI, 0.23-0.92]) and 24-month (0.64 [95% CI, 0.46-0.88]) interval cancer. CONCLUSION: Two-view mammography for first and subsequent screens is associated with lower rates of interval breast cancer. This is at the expense of an increased number of women being recalled for further assessment after subsequent screens.

Analysis of the effect of age on the prognosis of breast cancer.

To explore the effect of age at diagnosis on relative survival from breast cancer at different cancer stages and grades, using appropriate statistical modeling of time-varying and non-linear effects of that prognostic covariate. Data on 4,791 female invasive breast cancers diagnosed between 1990 and 1997 were obtained from a French cancer registry. The effect of age on relative survival was studied using an approach based on excess rate modeling. Different models testing non-linear and non-proportional effects of age were explored for each grade and each stage. In the whole population, the effect of age was not linear and varied with the time elapsed since diagnosis. When analyzing the different sub-groups according to grade and stage, age did not have a significant effect on relative survival in grade 1 or stage 3 tumors. In grade 2 and stage 4 tumors, the excess mortality rate increased with age, in a linear way. In grade 3 tumors, age was a time-dependent factor: older women had higher excess rates than younger ones during the first year after diagnosis whereas the inverse phenomenon was observed 5 years after diagnosis. Our findings suggest that when taking into account grade and stage, the time-varying impact of young age at diagnosis is limited to grade 3 tumors, without evidence of worst prognosis at 5 years for the youngest women.