Population-Based Validation of the Prognostic Model ADJUVANT! for Early Breast Cancer

2005 ◽  
Vol 23 (12) ◽  
pp. 2716-2725 ◽  
Author(s):  
Ivo A. Olivotto ◽  
Chris D. Bajdik ◽  
Peter M. Ravdin ◽  
Caroline H. Speers ◽  
Andrew J. Coldman ◽  
...  
Keyword(s):  
Breast Cancer ◽  
British Columbia ◽  
Prognostic Factors ◽  
Systemic Therapy ◽  
Population Based ◽  
Adjuvant Systemic Therapy ◽  
Cancer Outcomes ◽  
Cancer Specific Survival ◽  
Breast Cancer Outcomes ◽  
Treatment Data

Purpose Adjuvant! ( www.adjuvantonline.com ) is a web-based tool that predicts 10-year breast cancer outcomes with and without adjuvant systemic therapy, but it has not been independently validated. Methods Using the British Columbia Breast Cancer Outcomes Unit (BCOU) database, demographic, pathologic, staging, and treatment data on 4,083 women diagnosed between 1989 and 1993 in British Columbia with T1-2, N0-1, M0 breast cancer were abstracted and entered into Adjuvant! to calculate predicted 10-year overall survival (OS), breast cancer–specific survival (BCSS), and event-free survival (EFS) for each patient. Individual BCOU observed outcomes at 10 years were independently determined. Predicted and observed outcomes were compared. Results Across all 4,083 patients, 10-year predicted and observed outcomes were within 1% for OS, BCSS, and EFS (all P > .05). Predicted and observed outcomes were within 2% for most demographic, pathologic, and treatment-defined subgroups. Adjuvant! overestimated OS, BCSS, and EFS in women younger than age 35 years (predicted − observed = 8.6%, 9.6%, and 13.6%, respectively; all P < .001) or with lymphatic or vascular invasion (LVI; predicted − observed = 3.6%, 3.8%, and 4.2%, respectively; all P < .05); these two prognostic factors were not automatically incorporated within the Adjuvant! algorithm. After adjusting for the distribution of LVI, using the prognostic factor impact calculator in Adjuvant!, 10-year predicted and observed outcomes were no longer significantly different. Conclusion Adjuvant! performed reliably. Patients younger than age 35 or with known additional adverse prognostic factors such as LVI require adjustment of risks to derive reliable predictions of prognosis without adjuvant systemic therapy and the absolute benefits of adjuvant systemic therapy.

Abstract PS7-29: Racial disparities in breast cancer outcomes: A SEER population based study

2021 ◽  
Author(s):  
Medhavi Gupta ◽  
Rohit Gosain ◽  
Maithreyi Sarma ◽  
Stuthi Perimbeti ◽  
Kristopher Attwood ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Racial Disparities ◽  
Population Based ◽  
Cancer Outcomes ◽  
Population Based Study ◽  
Breast Cancer Outcomes

scholarly journals Latinas and Breast Cancer Outcomes: Population-Based Sampling, Ethnic Identity, and Acculturation Assessment

2009 ◽  
Vol 18 (7) ◽  
pp. 2022-2029 ◽  
Author(s):  
Ann S. Hamilton ◽  
Timothy P. Hofer ◽  
Sarah T. Hawley ◽  
Donna Morrell ◽  
Meryl Leventhal ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ethnic Identity ◽  
Population Based ◽  
Cancer Outcomes ◽  
Breast Cancer Outcomes

scholarly journals Obesity and breast cancer outcomes in chemotherapy patients in New Zealand – a population-based cohort study

BMC Cancer ◽  
2018 ◽  
Vol 18 (1) ◽  
Author(s):  
J. Mark Elwood ◽  
Sandar Tin Tin ◽  
Marion Kuper-Hommel ◽  
Ross Lawrenson ◽  
Ian Campbell
Keyword(s):  
Breast Cancer ◽  
Cohort Study ◽  
New Zealand ◽  
Population Based ◽  
Cancer Outcomes ◽  
Breast Cancer Outcomes ◽  
Chemotherapy Patients

scholarly journals In Patients Younger Than Age 55 Years With Lymph Node–Negative Breast Cancer, Proliferation by Mitotic Activity Index Is Prognostically Superior to Adjuvant!

2011 ◽  
Vol 29 (7) ◽  
pp. 852-858 ◽  
Author(s):  
Tone Hoel Lende ◽  
Emiel A.M. Janssen ◽  
Einar Gudlaugsson ◽  
Feja Voorhorst ◽  
Rune Smaaland ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Mitotic Activity ◽  
Systemic Therapy ◽  
Activity Index ◽  
Multivariable Analysis ◽  
Adjuvant Systemic Therapy ◽  
Cancer Proliferation ◽  
Cancer Specific Survival ◽  
Mitotic Activity Index

PurposeIn breast cancer, different tools are used for prognostication and adjuvant systemic therapy selection. We compared the accuracy of the online program Adjuvant!, the Norwegian Breast Cancer Group (NBCG) guidelines, and the proliferation factor mitotic activity index (MAI) in patients with lymph node (LN) –negative disease (pN0).Patients and MethodsAdjuvant! and MAI thresholds were set to 90% to 95% breast cancer–specific survival (BCSS) rates. These thresholds were 95% for Adjuvant!, 3 for MAI, and as follows for NBCG: pT1 grade 1 + pT1a-b grade 2 to 3; all pN0M0 and estrogen receptor/progesterone receptor positive versus all others. In 516 patients younger than age 55 years (T1-3N0M0) without adjuvant systemic therapy, univariable and multivariable 10-year BCSS rates were estimated.ResultsMedian follow-up time was 118 months. The concordance between MAI and Adjuvant! or NBCG was fair (κ = 0.35 and κ = 0.29, respectively). Adjuvant!, NBCG, and MAI were all prognostically significant (P ≤ .001). In the univariable analysis, the 10-year BCSS of MAI less than 3 versus ≥ 3 was 95% v 71%, respectively, with a hazard ratio of 7.0. In multivariable analysis, MAI was superior to Adjuvant! and NBCG. The 10-year survival of Adjuvant! ≥ 95% versus less than 95% was 91% v 74%, respectively, but stratification by MAI identified subgroups with different prognosis. Similar results occurred for NBCG and MAI. Adjuvant! and NBCG were not prognostic to each other.ConclusionMAI is superior to Adjuvant! and NBCG in prognostication of patients with LN-negative breast cancer younger than age 55 years.

scholarly journals Opportunities for improving triple-negative breast cancer outcomes: results of a population-based study

2017 ◽  
Vol 6 (3) ◽  
pp. 526-536 ◽  
Author(s):  
Elisabetta Rapiti ◽  
Kim Pinaud ◽  
Pierre O. Chappuis ◽  
Valeria Viassolo ◽  
Aurélie Ayme ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Population Based ◽  
Cancer Outcomes ◽  
Population Based Study ◽  
Breast Cancer Outcomes

Influence of young age at diagnosis and family history of breast or ovarian cancer on breast cancer outcomes in a population-based cohort study

2006 ◽  
Vol 105 (1) ◽  
pp. 69-80 ◽  
Author(s):  
Jane C. Figueiredo ◽  
Marguerite Ennis ◽  
Julia A. Knight ◽  
John R. McLaughlin ◽  
Nicky Hood ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Cohort Study ◽  
Family History ◽  
Population Based ◽  
Young Age ◽  
Age At Diagnosis ◽  
Cancer Outcomes ◽  
Breast Cancer Outcomes ◽  
History Of

Overall Survival and Cause-Specific Mortality of Patients With Stage T1a,bN0M0 Breast Carcinoma

2007 ◽  
Vol 25 (31) ◽  
pp. 4952-4960 ◽  
Author(s):  
Emer O. Hanrahan ◽  
Ana M. Gonzalez-Angulo ◽  
Sharon H. Giordano ◽  
Roman Rouzier ◽  
Kristine R. Broglio ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Systemic Therapy ◽  
Seer Program ◽  
Adjuvant Systemic Therapy ◽  
Locoregional Therapy ◽  
Breast Cancer Specific Survival ◽  
Cancer Specific Survival ◽  
The Impact ◽  
Related Mortality

Purpose With mammographic screening, the frequency of diagnosis of stage T1a,bN0M0 breast cancer has increased. Prognosis after locoregional therapy and benefit from adjuvant systemic therapy are poorly defined. We reviewed T1a,bN0M0 breast cancer cases registered in the Surveillance, Epidemiology, and End Results (SEER) Program to investigate the impact of prognostic factors on breast cancer–specific (BCSM) and non–breast cancer–related mortality. Methods We identified T1a,bN0M0 breast cancer cases registered in the SEER Program from 1988 to 2001, and used the Kaplan-Meier product limit method to describe overall survival (OS). We estimated the probabilities of death resulting from breast cancer and from other causes, and analyzed associations of patient and tumor characteristics with OS, BCSM, and non–breast cancer–related mortality using the log-rank test, Cox proportional hazards models, and a competing-risk model. We constructed nomograms to assist physicians in adjuvant therapy decision making. Results We identified 51,246 T1a,bN0M0 cases. Median follow-up was 64 months (range, 1 to 167 months). Median age at diagnosis was 65 years (range, 20 to 101 years). Ten-year probabilities of all-cause mortality and BCSM were 24% and 4%, respectively. Characteristics associated with increased probability of BCSM included age younger than 50 years at diagnosis, high tumor grade, estrogen receptor–negative status, progesterone receptor–negative status, and fewer than six nodes removed at axillary dissection. The constructed nomograms allow a comparison of predicted breast cancer–specific survival and non-breast cancer–specific survival in individual patients. Conclusion Overall, the prognosis of patients with T1a,bN0M0 breast cancer is excellent. However, subgroups of patients who are at higher risk of BCSM and who should be considered for adjuvant systemic therapy can be identified.

scholarly journals Impact of changing from annual to biennial mammographic screening on breast cancer outcomes in women aged 50–79 in British Columbia

2008 ◽  
Vol 15 (4) ◽  
pp. 182-187 ◽  
Author(s):  
Andrew J Coldman ◽  
Norm Phillips ◽  
Ivo A Olivotto ◽  
Paula Gordon ◽  
Linda Warren ◽  
...  
Keyword(s):  
Breast Cancer ◽  
British Columbia ◽  
Cancer Mortality ◽  
Breast Cancer Mortality ◽  
Mortality Rates ◽  
Screening Mammography ◽  
Axillary Node ◽  
Age Group ◽  
Cancer Outcomes ◽  
Breast Cancer Outcomes

Objectives The objective of this study was to compare breast cancer outcomes among women subject to different policies on mammography screening frequency. Setting Data were obtained for women participating in the Screening Mammography Programme of British Columbia (SMPBC) for 1988–2005. The SMPBC changed its policy for women aged 50–79 years from annual to biennial mammography in 1997, but retained an annual recommendation for women aged 40–49 years. Methods Breast cancer outcomes were compared for women participating in the programme before and after 1997 for two groups: ages 40–49 and 50–79 years. Results There were data on 658,151 women. Comparing pre-1997 and post-1997, the median interscreen interval increased by 11.1 months in women 50–79 but by only 0.3 months in women aged 40–49. Excluding those detected at initial screen, 6291 breast cancers were identified. Comparing pre-1997 and post-1997: the relative rates (RR) of screen detected cancer increased in women aged 40–49 (RR = 1.32) and the rate of invasive cancers ≥20 mm at diagnosis decreased (RR = 0.83); the rate of cancers with axillary node involvement increased in women aged 50–79 (RR = 1.23). Cancer survival improved after 1997 for women diagnosed at ages 40–49 (hazard ratio = 0.62), but was unchanged for women aged 50–79. Breast cancer mortality rates did not change between the periods in either age group. Conclusion The proximal cancer outcomes considered (staging and survival) improved in women aged 40–49 but this was offset in women aged 50–79 associated with the change in screen frequency. These changes did not result in alterations in breast cancer mortality rates in either age group.

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