- Email: [email protected]
P5 Estimating five- and nine-year survival in older women with breast cancer using cancer-specific geriatric assessment
S20
Critical Reviews in Oncology/Hematology 72S1 (2009)
of primitive tumour. Seventy-one patients (76.4%) presented with early disease. Fifty-six patients (60.2%) were able to complete VES-13 autonomously, 7 patients (7.5%) required help in some questions while in 30 cases (32.2%) the questionnaire was completely administered by research nurse. The median time required to perform VES-13 was 5.3 minutes (range 1−12) compared to 25 minutes (range 10−72) spent for CGA. The table shows that the VES-13 could be able to detect 69% of fit, 42% of vulnerable and 79% of frail patients. VES-13 Favourable (score 3) Unfavourable (score <3) Total
CGA Fit
Vulnerable
Frail
Total
37 (69.8%) 16 (30.2%) 53 (100%)
12 (57.1%) 9 (42.9%) 21 (100%)
4 (21.0%) 15 (79.0%) 19 (100%)
53 (57.0%) 40 (43.0%) 93 (100%)
Sensibility and specificity of VES-13 to uncover vulnerability/frailty at full CGA were 60% and 70%, respectively. The positive and negative predictive values were 60% and 70%, respectively. Conclusions: VES-13 significantly reduces the time of geriatric assessment, but up to one third of elderly cancer patients had significant troubles in self-compiling the questionnaire. Since, VES-13 showed rather unsatisfactory sensitivity and specificity, caution should be recommended in using VES-13 as a substitute for full CGA in both everyday practice and clinical trials. P5 Estimating five- and nine-year survival in older women with breast cancer using cancer-specific geriatric assessment K.M. Clough-Gorr1,2,3 *, R.A. Silliman1 *. 1 Geriatrics Section, Boston University Medical Center, Boston, MA 02118, USA, 2 Institute of Social and Preventive Medicine (ISPM), University of Bern, CH3012 Bern, Switzerland, 3 Department of Geriatrics, Inselspital University of Bern Hospital, CH3010 Bern, Switzerland Background: The fastest growing segment of the U.S. population is adults 65 years or older, projected to be 20% by 2030.1 Among this population of older adults, cancer is the second leading cause of death; breast cancer is the most common type among older women.2 Older cancer patients are heterogeneous.3−5 Applying geriatric principles to oncology care weighs the impact of known care-influencing factors such as comorbidity (i.e., vulnerability to adverse treatment effects) or social support (i.e., ability to get to treatments), in relation to overall life expectancy.6−8 Little is known about the accuracy of estimating life expectancy based on cancerspecific geriatric assessment (CGA). Taking advantage of GA tools that include cancer-specific risk (i.e., age and stage) may help to individualize treatment, as well as identify strategies for risk factor modification.9−11 Objective: To estimate five- and nine-year survival based on CGA in older women with breast cancer. Design: Secondary analysis of baseline, five- and nine-year data from a longitudinal follow-up study of older women with breast cancer. Participants: We identified women diagnosed with primary breast cancer in four geographic regions in the U.S.A. (Los Angeles, California; Minnesota; North Carolina; Rhode Island) and selected 660 with: (1) stage I (tumor diameter 1 cm), stage II, or stage IIIa disease, (2) age 65 years or older on the date of diagnosis, and (3) permission from the attending physician to contact. Measurement: Data were collected over nine-years of follow-up from consenting women’s medical records, telephone interviews, National Death Index and Social Security Death Index. CGA was described by five domains using eight measures: cancer-specific (age, stage); socio-demographic (financial resources); clinical (comorbidity, obesity); function (physical function limitations), and psychosocial (general mental health, social support). The outcomes were five- and nine-year all-cause mortality. Potential confounding factors included collected non-GA assessment measures such as site, race, education, marital status, self-rated health, and breast cancer therapy. Analysis: Analyses included log-rank tests, Cochran-Armitage test-oftrend Kaplan-Meier survivor functions, univariate and multivariate Cox
10th SIOG Meeting, October 15–17, 2009, Berlin, Germany proportional hazards regression. Final models included variables based on two criteria: (1) a theoretical basis for, or knowledge of a relation between causal variables and effects, and (2) statistical testing (i.e., elimination of highly correlated variables, inclusion of a necessary minimum set of statistically meaningful variables, and overall model fit). Results: The risk of death at both five- and nine-years was considerably higher in women with 3CGA baseline domain deficits (HR5−yr = 2.46 [95& CI 1.67–3.62], HR9−yr = 2.98 [2.20–4.05]). The probability of surviving was consistently statistically significantly lower in women with 3 deficits in CGA domains at baseline (five-years: 75% vs. 89%; nineyears: 57% vs. 82%, p < 0.0001). The proportion of women surviving significantly decreased as the number of deficits in baseline CGA domains increased (linear trend p < 0.0001). Conclusion: This study provides longitudinal evidence that CGA can predict five- and nine-year life expectancy in older women with breast cancer. Hence, CGA may provide an effective strategy to guide treatment decision-making and to identifying risk factors for intervention. Reference(s) [1] A Profile of Older Americans: 2007. Washington, D.C.: Administration on Aging (AoA), U.S. Department of Health and Human Services; 2007. [2] Breast Cancer Facts & Figures. www.cancer.org, 2008. [3] Hurria A, Lichtman SM, Gardes J, et al. Identifying vulnerable older adults with cancer: integrating geriatric assessment into oncology practice. J Am Geriatr Soc. Oct 2007;55(10):1604–1608. [4] Balducci L, Beghe C. Cancer and age in the USA. Crit Rev Oncol Hematol. Feb 2001;37(2):137–145. [5] Klepin H, Mohile S, Hurria A. Geriatric assessment in older patients with breast cancer. J Natl Compr Canc Netw. Feb 2009;7(2):226–236. [6] Huss A, Stuck AE, Rubenstein LZ, Egger M, Clough-Gorr KM. Multidimensional preventive home visit programs for community-dwelling older adults: a systematic review and meta-analysis of randomized controlled trials. J Gerontol A Biol Sci Med Sci. Mar 2008;63(3):298–307. [7] Stuck AE, Siu AL, Wieland GD, Adams J, Rubenstein LZ. Comprehensive geriatric assessment: a meta-analysis of controlled trials. Lancet. Oct 23 1993;342(8878):1032–1036. [8] Wieland D, Hirth V. Comprehensive geriatric assessment. Cancer Control. NovDec 2003;10(6):454–462. [9] Chen CC, Kenefick AL, Tang ST, McCorkle R. Utilization of comprehensive geriatric assessment in cancer patients. Crit Rev Oncol Hematol. Jan 2004;49(1):53−67. [10] Extermann M, Aapro M, Bernabei R, et al. Use of comprehensive geriatric assessment in older cancer patients: recommendations from the task force on CGA of the International Society of Geriatric Oncology (SIOG). Crit Rev Oncol Hematol. Sep 2005;55(3):241–252. [11] Extermann M, Hurria A. Comprehensive geriatric assessment for older patients with cancer. J Clin Oncol. May 10 2007;25(14):1824–1831.
P6 Results from a pilot study of a brief Cancer-Specific Geriatric Assessment (CGA) tool for use in clinical trials of older cancer patients F. Hitz1 *, U. Mey2 *, K.M. Clough-Gorr3,4,5 . 1 Department of Oncology, Kantonsspital SG, St. Gallen, Switzerland, 2 Medical Oncology, Kantonsspital Graub¨unden, Chur, Switzerland, 3 Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland, 4 Geriatrics Section, Boston University Medical Center, Boston, MA, USA, 5 Department of Geriatrics, Inselspital University of Bern Hospital, Bern, Switzerland Background: Although risk of cancer increases with age, and industrialized populations are rapidly aging, the growing population of older cancer patients is grossly underrepresented in clinical trials. Moreover, trials including older cancer patients seldom incorporate geriatric principles. Multidimensional geriatric assessment has been shown in general population studies to be a promising tool of assessment domains capturing a range of patient factors resulting in an individualized interventionplan for optimizing clinical management and outcomes.1−3 Yet currently there is little cancer-specific geriatric assessment (CGA) efficacy data and no published reports of instruments designed specifically for use in clinical trials.4−6 An urgent need exists for prospective studies to determine CGA’s ability to predict relevant outcomes such as choice of treatment, treatment tolerance, treatment completion, survival, and quality of life.4,7−9 Incorporating standardized CGA into clinical trials of older
Critical Reviews in Oncology/Hematology 72S1 (2009)
of primitive tumour. Seventy-one patients (76.4%) presented with early disease. Fifty-six patients (60.2%) were able to complete VES-13 autonomously, 7 patients (7.5%) required help in some questions while in 30 cases (32.2%) the questionnaire was completely administered by research nurse. The median time required to perform VES-13 was 5.3 minutes (range 1−12) compared to 25 minutes (range 10−72) spent for CGA. The table shows that the VES-13 could be able to detect 69% of fit, 42% of vulnerable and 79% of frail patients. VES-13 Favourable (score 3) Unfavourable (score <3) Total
CGA Fit
Vulnerable
Frail
Total
37 (69.8%) 16 (30.2%) 53 (100%)
12 (57.1%) 9 (42.9%) 21 (100%)
4 (21.0%) 15 (79.0%) 19 (100%)
53 (57.0%) 40 (43.0%) 93 (100%)
Sensibility and specificity of VES-13 to uncover vulnerability/frailty at full CGA were 60% and 70%, respectively. The positive and negative predictive values were 60% and 70%, respectively. Conclusions: VES-13 significantly reduces the time of geriatric assessment, but up to one third of elderly cancer patients had significant troubles in self-compiling the questionnaire. Since, VES-13 showed rather unsatisfactory sensitivity and specificity, caution should be recommended in using VES-13 as a substitute for full CGA in both everyday practice and clinical trials. P5 Estimating five- and nine-year survival in older women with breast cancer using cancer-specific geriatric assessment K.M. Clough-Gorr1,2,3 *, R.A. Silliman1 *. 1 Geriatrics Section, Boston University Medical Center, Boston, MA 02118, USA, 2 Institute of Social and Preventive Medicine (ISPM), University of Bern, CH3012 Bern, Switzerland, 3 Department of Geriatrics, Inselspital University of Bern Hospital, CH3010 Bern, Switzerland Background: The fastest growing segment of the U.S. population is adults 65 years or older, projected to be 20% by 2030.1 Among this population of older adults, cancer is the second leading cause of death; breast cancer is the most common type among older women.2 Older cancer patients are heterogeneous.3−5 Applying geriatric principles to oncology care weighs the impact of known care-influencing factors such as comorbidity (i.e., vulnerability to adverse treatment effects) or social support (i.e., ability to get to treatments), in relation to overall life expectancy.6−8 Little is known about the accuracy of estimating life expectancy based on cancerspecific geriatric assessment (CGA). Taking advantage of GA tools that include cancer-specific risk (i.e., age and stage) may help to individualize treatment, as well as identify strategies for risk factor modification.9−11 Objective: To estimate five- and nine-year survival based on CGA in older women with breast cancer. Design: Secondary analysis of baseline, five- and nine-year data from a longitudinal follow-up study of older women with breast cancer. Participants: We identified women diagnosed with primary breast cancer in four geographic regions in the U.S.A. (Los Angeles, California; Minnesota; North Carolina; Rhode Island) and selected 660 with: (1) stage I (tumor diameter 1 cm), stage II, or stage IIIa disease, (2) age 65 years or older on the date of diagnosis, and (3) permission from the attending physician to contact. Measurement: Data were collected over nine-years of follow-up from consenting women’s medical records, telephone interviews, National Death Index and Social Security Death Index. CGA was described by five domains using eight measures: cancer-specific (age, stage); socio-demographic (financial resources); clinical (comorbidity, obesity); function (physical function limitations), and psychosocial (general mental health, social support). The outcomes were five- and nine-year all-cause mortality. Potential confounding factors included collected non-GA assessment measures such as site, race, education, marital status, self-rated health, and breast cancer therapy. Analysis: Analyses included log-rank tests, Cochran-Armitage test-oftrend Kaplan-Meier survivor functions, univariate and multivariate Cox
10th SIOG Meeting, October 15–17, 2009, Berlin, Germany proportional hazards regression. Final models included variables based on two criteria: (1) a theoretical basis for, or knowledge of a relation between causal variables and effects, and (2) statistical testing (i.e., elimination of highly correlated variables, inclusion of a necessary minimum set of statistically meaningful variables, and overall model fit). Results: The risk of death at both five- and nine-years was considerably higher in women with 3CGA baseline domain deficits (HR5−yr = 2.46 [95& CI 1.67–3.62], HR9−yr = 2.98 [2.20–4.05]). The probability of surviving was consistently statistically significantly lower in women with 3 deficits in CGA domains at baseline (five-years: 75% vs. 89%; nineyears: 57% vs. 82%, p < 0.0001). The proportion of women surviving significantly decreased as the number of deficits in baseline CGA domains increased (linear trend p < 0.0001). Conclusion: This study provides longitudinal evidence that CGA can predict five- and nine-year life expectancy in older women with breast cancer. Hence, CGA may provide an effective strategy to guide treatment decision-making and to identifying risk factors for intervention. Reference(s) [1] A Profile of Older Americans: 2007. Washington, D.C.: Administration on Aging (AoA), U.S. Department of Health and Human Services; 2007. [2] Breast Cancer Facts & Figures. www.cancer.org, 2008. [3] Hurria A, Lichtman SM, Gardes J, et al. Identifying vulnerable older adults with cancer: integrating geriatric assessment into oncology practice. J Am Geriatr Soc. Oct 2007;55(10):1604–1608. [4] Balducci L, Beghe C. Cancer and age in the USA. Crit Rev Oncol Hematol. Feb 2001;37(2):137–145. [5] Klepin H, Mohile S, Hurria A. Geriatric assessment in older patients with breast cancer. J Natl Compr Canc Netw. Feb 2009;7(2):226–236. [6] Huss A, Stuck AE, Rubenstein LZ, Egger M, Clough-Gorr KM. Multidimensional preventive home visit programs for community-dwelling older adults: a systematic review and meta-analysis of randomized controlled trials. J Gerontol A Biol Sci Med Sci. Mar 2008;63(3):298–307. [7] Stuck AE, Siu AL, Wieland GD, Adams J, Rubenstein LZ. Comprehensive geriatric assessment: a meta-analysis of controlled trials. Lancet. Oct 23 1993;342(8878):1032–1036. [8] Wieland D, Hirth V. Comprehensive geriatric assessment. Cancer Control. NovDec 2003;10(6):454–462. [9] Chen CC, Kenefick AL, Tang ST, McCorkle R. Utilization of comprehensive geriatric assessment in cancer patients. Crit Rev Oncol Hematol. Jan 2004;49(1):53−67. [10] Extermann M, Aapro M, Bernabei R, et al. Use of comprehensive geriatric assessment in older cancer patients: recommendations from the task force on CGA of the International Society of Geriatric Oncology (SIOG). Crit Rev Oncol Hematol. Sep 2005;55(3):241–252. [11] Extermann M, Hurria A. Comprehensive geriatric assessment for older patients with cancer. J Clin Oncol. May 10 2007;25(14):1824–1831.
P6 Results from a pilot study of a brief Cancer-Specific Geriatric Assessment (CGA) tool for use in clinical trials of older cancer patients F. Hitz1 *, U. Mey2 *, K.M. Clough-Gorr3,4,5 . 1 Department of Oncology, Kantonsspital SG, St. Gallen, Switzerland, 2 Medical Oncology, Kantonsspital Graub¨unden, Chur, Switzerland, 3 Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland, 4 Geriatrics Section, Boston University Medical Center, Boston, MA, USA, 5 Department of Geriatrics, Inselspital University of Bern Hospital, Bern, Switzerland Background: Although risk of cancer increases with age, and industrialized populations are rapidly aging, the growing population of older cancer patients is grossly underrepresented in clinical trials. Moreover, trials including older cancer patients seldom incorporate geriatric principles. Multidimensional geriatric assessment has been shown in general population studies to be a promising tool of assessment domains capturing a range of patient factors resulting in an individualized interventionplan for optimizing clinical management and outcomes.1−3 Yet currently there is little cancer-specific geriatric assessment (CGA) efficacy data and no published reports of instruments designed specifically for use in clinical trials.4−6 An urgent need exists for prospective studies to determine CGA’s ability to predict relevant outcomes such as choice of treatment, treatment tolerance, treatment completion, survival, and quality of life.4,7−9 Incorporating standardized CGA into clinical trials of older