OBJECTIVES: Lymphedema is a common complication of breast cancer surgery, leading to a decreased quality of life. The risk and severity of lymphedema were associated with surgery side upper extremity infection, ≥25 kg/m(2) body mass index (BMI), and the level of hand use (LHU). Our aim was to estimate the probability of lymphedema after breast cancer surgery by using previously published incidence rates and these 3 risk factors. METHODS: The design was a n:m matched case control study; data were analyzed on 51 patients with lymphedema and 126 available controls matched on age, radiation therapy, and operation type. In conjunction with published estimates of lymphedema, incidence rates, and estimates of the proportions of risk factor combinations in cases and controls, the Bayes' theorem was used to estimate the probability of developing lymphedema. RESULTS: Lymphedema probabilities of 7 combinations for 6 different published calculations were used. With the assumption of 16% LE incidence rate of lymphedema, a BMI<25, no infection, and a low LHU, the estimated probability of lymphedema was 6.8%. With the assumption of 46.3% LE incidence a BMI ≥25, infection, and a high LHU led to an estimated lymphedema probability of 93.7%. CONCLUSIONS: This study shows that control of predisposing factors in both high and low incidence rates has a marked effect on the probability of LE development. In other words, patients with low incidence for LE are more prone to develop LE if the predisposing factors are controlled poorly compared to the high incidence patients whom the predisposing factors are avoided.
OBJECTIVES:Lymphedema is a common complication of breast cancer surgery, leading to a decreased quality of life. The risk and severity of lymphedema were associated with surgery side upper extremity infection, ≥25 kg/m(2) body mass index (BMI), and the level of hand use (LHU). Our aim was to estimate the probability of lymphedema after breast cancer surgery by using previously published incidence rates and these 3 risk factors. METHODS: The design was a n:m matched case control study; data were analyzed on 51 patients with lymphedema and 126 available controls matched on age, radiation therapy, and operation type. In conjunction with published estimates of lymphedema, incidence rates, and estimates of the proportions of risk factor combinations in cases and controls, the Bayes' theorem was used to estimate the probability of developing lymphedema. RESULTS:Lymphedema probabilities of 7 combinations for 6 different published calculations were used. With the assumption of 16% LE incidence rate of lymphedema, a BMI<25, no infection, and a low LHU, the estimated probability of lymphedema was 6.8%. With the assumption of 46.3% LE incidence a BMI ≥25, infection, and a high LHU led to an estimated lymphedema probability of 93.7%. CONCLUSIONS: This study shows that control of predisposing factors in both high and low incidence rates has a marked effect on the probability of LE development. In other words, patients with low incidence for LE are more prone to develop LE if the predisposing factors are controlled poorly compared to the high incidence patients whom the predisposing factors are avoided.
Authors: Ji-Bin Liu; Daniel A Merton; Adam C Berger; Flemming Forsberg; Agnieszka Witkiewicz; Hongjia Zhao; John R Eisenbrey; Traci B Fox; Barry B Goldberg Journal: J Ultrasound Med Date: 2014-06 Impact factor: 2.153
Authors: Marek Ancukiewicz; Cynthia L Miller; Melissa N Skolny; Jean O'Toole; Laura E Warren; Lauren S Jammallo; Michelle C Specht; Alphonse G Taghian Journal: Breast Cancer Res Treat Date: 2012-06-19 Impact factor: 4.872
Authors: Jean O'Toole; Lauren S Jammallo; Melissa N Skolny; Cynthia L Miller; Krista Elliott; Michelle C Specht; Alphonse G Taghian Journal: Crit Rev Oncol Hematol Date: 2013-06-16 Impact factor: 6.312
Authors: Daniella M F Paiva; Vivian O Rodrigues; Marcelle G Cesca; Pamella V Palma; Isabel C G Leite Journal: BMC Womens Health Date: 2013-02-13 Impact factor: 2.809
Authors: Michelle C Specht; Cynthia L Miller; Tara A Russell; Nora Horick; Melissa N Skolny; Jean A O'Toole; Lauren S Jammallo; Andrzej Niemierko; Betro T Sadek; Mina N Shenouda; Dianne M Finkelstein; Barbara L Smith; Alphonse G Taghian Journal: Breast Cancer Res Treat Date: 2013-08-04 Impact factor: 4.872
Authors: Chantal M Ferguson; Meyha N Swaroop; Nora Horick; Melissa N Skolny; Cynthia L Miller; Lauren S Jammallo; Cheryl Brunelle; Jean A O'Toole; Laura Salama; Michelle C Specht; Alphonse G Taghian Journal: J Clin Oncol Date: 2015-12-07 Impact factor: 44.544
Authors: Melissa B Aldrich; Renie Guilliod; Caroline E Fife; Erik A Maus; Latisha Smith; John C Rasmussen; Eva M Sevick-Muraca Journal: Biomed Opt Express Date: 2012-05-03 Impact factor: 3.732