BACKGROUND: While women aged 50 and older are broadly considered to benefit from screening mammograms, the evidence of any similar advantages for younger women are still considered insufficient to form any substantial conclusions on the matter. The primary goal of this study was to examine whether or not the mortality rate of younger women is benefited by mammography, and if so, how can this beneficial effect be maximized. METHODS: The authors have taken into account all available randomized control trials (RCTs) and have conducted a meta-analysis based on those RCTs to study the effect of mammography on the mortality rate of women younger than age 50. Further interpretation on various aspects of the results has also led to separate meta-analyses, with the RCTs included grouped in accordance to the mean time interval between screening mammograms employed by each study. The findings and conclusions of the comparison were used to calculate the number of mammograms necessary to reduce the absolute death risk, depending on the time interval between screening mammograms. RESULTS: The meta-analysis indicated a reduction in breast-cancer mortality in the intervention group, which reached statistical significance (relative risk (RR) 0.81 [95% CI 0.71-0.93] p < 0.01). Furthermore, when the RCTs included were grouped according to their mean time interval between mammograms, there was a definite increase of statistical significance in favor of those RCTs with shorter interval times (RR 0.76 [95% CI 0.64-0.89] p < 0.01). CONCLUSIONS: The significant mortality rate reduction demonstrated by the meta-analytical results is a key indicator of the beneficial effect of mammography on the age group of women younger than 50. Additionally, the increase in the aforesaid significance when combining RCTs with short time intervals between mammograms, as opposed to those RCTs with longer intervals, suggests that the optimal use of mammographic screening lies with the former. This is better demonstrated when taking in account our approach to answering the practical question of "how many screening mammograms will take to save one life?" in correlation with the mean time interval involved.
BACKGROUND: While women aged 50 and older are broadly considered to benefit from screening mammograms, the evidence of any similar advantages for younger women are still considered insufficient to form any substantial conclusions on the matter. The primary goal of this study was to examine whether or not the mortality rate of younger women is benefited by mammography, and if so, how can this beneficial effect be maximized. METHODS: The authors have taken into account all available randomized control trials (RCTs) and have conducted a meta-analysis based on those RCTs to study the effect of mammography on the mortality rate of women younger than age 50. Further interpretation on various aspects of the results has also led to separate meta-analyses, with the RCTs included grouped in accordance to the mean time interval between screening mammograms employed by each study. The findings and conclusions of the comparison were used to calculate the number of mammograms necessary to reduce the absolute death risk, depending on the time interval between screening mammograms. RESULTS: The meta-analysis indicated a reduction in breast-cancer mortality in the intervention group, which reached statistical significance (relative risk (RR) 0.81 [95% CI 0.71-0.93] p < 0.01). Furthermore, when the RCTs included were grouped according to their mean time interval between mammograms, there was a definite increase of statistical significance in favor of those RCTs with shorter interval times (RR 0.76 [95% CI 0.64-0.89] p < 0.01). CONCLUSIONS: The significant mortality rate reduction demonstrated by the meta-analytical results is a key indicator of the beneficial effect of mammography on the age group of women younger than 50. Additionally, the increase in the aforesaid significance when combining RCTs with short time intervals between mammograms, as opposed to those RCTs with longer intervals, suggests that the optimal use of mammographic screening lies with the former. This is better demonstrated when taking in account our approach to answering the practical question of "how many screening mammograms will take to save one life?" in correlation with the mean time interval involved.
Authors: Stephane Zervoudis; George Iatrakis; Eirini Tomara; Anastasia Bothou; George Papadopoulos; George Tsakiris Journal: World J Clin Oncol Date: 2014-08-10
Authors: Stephen Duffy; Daniel Vulkan; Howard Cuckle; Dharmishta Parmar; Shama Sheikh; Robert Smith; Andrew Evans; Oleg Blyuss; Louise Johns; Ian Ellis; Peter Sasieni; Chris Wale; Jonathan Myles; Sue Moss Journal: Health Technol Assess Date: 2020-10 Impact factor: 4.014
Authors: Stephen W Duffy; Daniel Vulkan; Howard Cuckle; Dharmishta Parmar; Shama Sheikh; Robert A Smith; Andrew Evans; Oleg Blyuss; Louise Johns; Ian O Ellis; Jonathan Myles; Peter D Sasieni; Sue M Moss Journal: Lancet Oncol Date: 2020-08-12 Impact factor: 41.316