Mammography-featured Natural History and Prognosis of Breast Cancer with Bayesian Markov Model
Date Issued
2014
Date
2014
Author(s)
Chuang, Shu-Lin
Abstract
Abstract
Background
In parallel with the evolution of breast cancer screening with mammography, temporal natural history of breast cancer and prognostic factors affecting the comparison of the difference of breast cancer survival between the screen-detected and the clinically-detected mode (two detection modes) are related to mammographic appearances. As conventional tumor attributes responsible for the prognosis of breast cancer are related to mammography-featured temporal natural history of breast cancer. It is therefore interesting to estimate the mean sojourn time and sensitivity by each type of mammographic appearance before explaining the difference of survival between the two detection modes for each type of mammography by considering the dynamics of these prognostic factors.
Objectives
The purposes of my thesis are (1) to develop Tabar-mammography-featured natural history of breast cancers taking sensitivity into account;(2) to assess how the difference between screen-detected and clinically detected cancer can be explained by conventional tumor attributes and treatment as well as mammographic appearance and the recently proposed tumor phenotypes and histological extent of tumor distribution; and (3) to throw light on the difference of breast cancer survival in the two detection modes, screen-detected and clinically-detected mode by Tabar classification of mammographic appearance of invasive breast cancer considering dynamics of these prognostic factors and the lead-time derived from the mean sojourn time allowing for sensitivity.
Methods
To model the simulation of the randomized controlled trial by inter-screening intervals and also the ability to detect early breast cancer (sensitivity) to improve the performance of screening to enhance the quality of screening procedure, we developed Bayesian directed acyclic graphic multistate Markov models (including three-state model and five-state model considering tumour size and node status) to estimate the mean sojourn time and sensitivity by different mammographic appearances by using Bayesian Gibbs sampling. These models were applied to data derived from a retrospective cohort from the original one of counties in the Swedish Two-county randomized controlled trial since 1977. Regarding the prognosis part, the prior estimates from 1977 and 1985 was further updated by the likelihood between 1996 and 1998 with data on new markers such as basal phenotype and histological tumor distribution, in addition to conventional tumor attributes, to spawn the updated posterior estimates with parametric Weibull survival model with Bayesian approach. The lead-time distribution derived from the sojourn time distribution was applied to make the comparison of the survival between the two detection modes.
Results
(1) The MST by mammographic appearance
The length of sojourn time is the longest for the stellate type (MST=5.61yrs) (95%CI: 4.40, 7.22), followed by powdery and crushed-stone-like type (MST=5.28 yrs) (95%CI: 3.02, 9.35), and the circular type (MST=3.60 yrs) (95%CI: 2.59, 5.15) without adjusting for sensitivity among small tumour less than 1.5 cm in the period of 1977-1985. The results found the highest sensitivity was noted in the powdery and crushed stone type (95.79% (95%CI: 82.00%, 99.29%)), followed by the circular type (95.24% (95%CI: 80.53, 99.29%)) and the least for the stellate type (83.42%, 95% CI: 66.42%, 95.70)) in the period of 1977-1985.
While the sensitivity was taken into account, the MST due to biological property for each type would turn to be longer. While the estimate of sensitivity by each type of mammographic appearance was considered the slowest progression was noted for the stellate type (MST=6.01 years) (95%CI: 4.23, 9.19), followed by the powdery and crushed stone type (MST=4.30) (95%CI: 2.42, 8.53) and the circular type (MST=3.03 years) (95%CI: 2.28, 5.19).
It is very interesting to note that the similar trend for the MST was observed for breast tumour smaller than 1.5 cm in the period of 1996-2010 but the MST was shorter in the period of 1996-2010 than that in the period of 1977-1985 and the sensitivity was improved to 95% or above.
The similar phenomenon was also observed for breast cancer with all size. The sensitivity was the highest in the powdery and crushed stone type (91.60%, 95%CI: 65.60%, 99.27%), followed by the stellate type (84.86%, 95%CI: 71.37%, 96.25%), and the lowest in the circular type (76.23%, 95%CI: 63.00%, 86.04%) in the period of 1977-1985. The MST was shorter in the period of 1996-2009 than that in the period of 1977-1985 and the sensitivity was improved to almost 100%.
For small breast tumour, the circular type is the highest and almost identical to the breast tumour larger than 1.5 cm for the transition from the PCDP to the CP. For all size breast tumour, the circular type was still the most rapid progression from the PCDP to the CP. The circular type was the highest I/E ratio. It requires an intensive screening and high sensitivity so as to reduce interval cancer compared with other types of mammographic appearance. The circular type was the poorest benefit of reducing breast tumour larger than 1.5 cm and node positive compared with the stellate type and the powdery and crushed stone type. When the inter-screening interval is lengthened to three years only 21% (95%CI: 2%, 0.35%) reduction for breast tumour larger than 1.5cm and 29% (6%, 46%) reduction for breast tumour with node positive.
(2) Assessing the possible factors in explanation of the difference between early-detected and clinical-detected breast cancers
In the early period of mammographic screening (1977-1995), the crude hazard ratio (HR) of breast cancer death for screen-detected cases compared with symptomatic ones was 0.22 (95% CI: 0.17, 0.29) compared with 0.53 (95% CI: 0.34, 0.76) when adjusted for conventional tumor attributes only. Using the data from the mature service screening period, 1996-98, the HR was 0.23 (95% CI: 0.08, 0.44) unadjusted and 0.71 (95% CI: 0.26, 1.47) after adjustment for tumor phenotype, mammographic appearance, histological tumor distribution, and conventional tumor attributes.
(3) Estimates for surrogates by mammographic appearance
Regarding the stellate type, the estimated HR for the two detection modes based on informative prior and the data on the period between 1996 and 1998 was 0.31 (95%CI: 0.20, 0.48) and was inflated to 0.57 (95%CI: 0.36, 0.89), making allowance for all other prognostic factors.
Similarly, the estimated HR for the circular type was 0.34 (95%CI: 0.20, 0.58) and was inflated to 0.51 (95%CI: 0.29, 0.89) after making allowance for conventional tumour attributes, treatment, tumour phenotype, and histological tumour distribution. As far as the casting type and architecture distortion are concerned, the estimated HR was 0.27 (95%CI: 0.15, 0.48) and was inflated to 0.39 (95%CI: 0.22, 0.69).
Conclusions
By using a novel Bayesian Markov models, the interplay between sensitivity and the mean sojourn time related to the progression from the PCDP to the CP for each type of mammographic appearance has been well elucidated. The results are heterogeneous. The average time for early detection of breast cancer within detectable window is longer for the stellate type whereas the detectable window for the circular type is short. The powdery and crush-stone-like is easily detected and the window of sojourn time for detection is also longer. The sensitivity for each type of mammographic appearance was improved up to at least 95% from the trial period to the service screening period. These transition parameters together with sensitivity are further applied to simulate the effect of inter-screening interval in combination with sensitivity on reducing interval cancer and also reducing tumour larger than 1.5 cm and node positive.
As the circular type has the shorter sojourn time intensive screening interval or high sensitivity is therefore required. Otherwise, the I/E ratio was higher and the benefit of screening was modest compared with other types of mammographic appearance.
Bayesian clinical reasoning approach was further adopted to make the comparison of survival of breast cancer between screen-detected breast cancer and clinically-detected ones while using information on conventional tumour attributes and also lead time distribution derived from the mean sojourn time.
Subjects
乳癌
乳房攝影表徵
存活分析
貝氏分析
多階段馬可夫模式
篩檢可偵測至臨床階段的平均滯留時間
敏感度
前導期偏差
SDGs
Type
thesis
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