Confirmation of a prognostic index for breast cancer

Galea, M.H.; Cw, Elston; Ellis, I.O.; Blamey, R. W.

doi:10.1016/0960-9776(92)90183-3

Cited by 2 publications

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“…Although historical data on size‐specific (Carter et al . 1989), NPI‐specific (Galea et al . 1991; Crisp et al .…”

Section: Discussionmentioning

confidence: 99%

“…Studies have shown that tumour size only accounts for 20% of the predictive value of the Nottingham index for survival, the remaining 80% are attributable to the impact of grade and nodal status (Haybitte et al 1982). Although historical data on size-specific (Carter et al 1989), NPI-specific (Galea et al 1991;Crisp et al 1993) survival or the presence of metastases (Dickman et al 1999) do exist, we felt that these data did not offer the same sensitivity as stage-specific data, moreover we could not be sure that they accurately reflected prognosis trends in our target population.…”

Section: Staging Informationmentioning

confidence: 99%

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Building a model to determine the cost-effectiveness of breast cancer screening in France

Arveux¹,

Wait²,

Schaffer³

2003

European Journal of Cancer Care

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This paper describes the methods and initial validation of a cost-effectiveness model developed to simulate the breast cancer screening situation in France. The first screening pilot programmes were set up in France in 1989 to test the feasibility of a decentralized screening model based in a large number of existing non-dedicated radiology centres. The present cost-effectiveness model was built as a tool to help guide current policy discussions on the future of screening in France. This Markov model compares the costs and effects expected when a screening programme is offered to a given cohort of women to those expected in the absence of screening. The model was initially validated using current results from the Bas-Rhin screening programme and local cancer registry epidemiological data. Over a 20-year period, 315 274 women would attend for screening, of whom 12 491 would be recalled for further assessment. 4423 cancers would be detected, resulting in 637 deaths. Screening allows the detection of 106 additional cancer cases, thereby preventing 92 deaths, and saves 1522 life-years compared with a situation without screening. Breast cancer mortality is reduced by 12.6%, yielding a cost-effectiveness ratio of 137 000 FF per life-year saved. The results of initial analyses suggest that the model is capable of suitably assessing the impact of breast cancer screening in terms of costs and effects. Further scenario analyses are needed to understand the impact of screening policy changes on the costs and effectiveness of future screening programmes.

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“…Although historical data on size‐specific (Carter et al . 1989), NPI‐specific (Galea et al . 1991; Crisp et al .…”

Section: Discussionmentioning

confidence: 99%

Section: Staging Informationmentioning

confidence: 99%

Building a model to determine the cost-effectiveness of breast cancer screening in France

Arveux¹,

Wait²,

Schaffer³

2003

European Journal of Cancer Care

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Correlation of OncotypeDx Recurrence Score, Nottingham Prognostic Index, and Ki67

2020

ABBSR

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Objective: To identify the correlation between the OncotypeDx Recurrence score, Nottingham Prognostic Index (NPI), and Ki67. Material & Methods: A retrospective study was conducted at Liaquat National Hospital where medical records of early-stage breast cancer patients, who had OncotypeDx RS done were reviewed from 2008-2019. The patient’s age, Histopathology type, tumor grade, size, No. of nodes involved, ER, PR, Her neu and Ki67 were collected. OncotypeDx RS, NPI, and Ki67 were categorized into 3 groups and statistical analysis was done to find a correlation between OncotypeDx RS, NPI and Ki67. Result: Total 76 patient’s records were reviewed. The average age of study participants was 56.40 ± 10.32 years. Oncotype-Dx method categorized 34 (44.74%), 26 (34.21%) and 16 (21.05%) patients as low, moderate and high risk respectively. 18(23.68%), 56(73.68) and 2(2.63%) were classified as low, moderate and high-risk patients by the NPI method correspondingly. According to Ki67, 26(40.63%), 21(32.81%) and 17(26.56%) patients were low, moderate and high risk respectively. Statistically significant fair agreement was only observed between Oncotype-Dx& Ki67 (k=0.33, p<0.001) with weak positive correlation (r=0.44, p<0.001). Further on age-stratification, it was observed that significant fair agreement (k=0.36, p<0.001) and weak positive correlation (r=0.45, p<0.001) between Oncotype-Dx& Ki67 risk assessment categories was for age group >50 years. On age stratification, moderate agreement (k=0.45, 0.002) and moderate correlation (r=0.57, p=0.005) were also observed between OncotypeDx& NPI risk categories for age group ≤50 years. Conclusion: No statistically significant strong agreement and correlation were observed among three risk assessment methods. Further investigations should be conducted with a larger sample size to assess agreement among these risk classification methods.

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Confirmation of a prognostic index for breast cancer

Cited by 2 publications

References 0 publications

Building a model to determine the cost-effectiveness of breast cancer screening in France

Building a model to determine the cost-effectiveness of breast cancer screening in France

Correlation of OncotypeDx Recurrence Score, Nottingham Prognostic Index, and Ki67

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