PROLARA: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure
Purpose To evaluate the impact of the reduced life expectancy of patients (compared to a nonpatient group with the same age distribution) on their nominal risk of developing cancer from the diagnostic use of radiation. Method We define a “prognosis-based lifetime attributable risk modifier” (PROLARM...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Eschner, Wolfgang [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2009 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag 2009 |
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| Übergeordnetes Werk: |
Enthalten in: European journal of nuclear medicine and molecular imaging - Heidelberg [u.a.] : Springer-Verl., 2002, 37(2009), 1 vom: 07. Aug. |
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| Übergeordnetes Werk: |
volume:37 ; year:2009 ; number:1 ; day:07 ; month:08 |
| Links: |
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| DOI / URN: |
10.1007/s00259-009-1221-y |
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SPR00313511X |
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| 100 | 1 | |a Eschner, Wolfgang |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a PROLARA: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure |
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| 500 | |a © Springer-Verlag 2009 | ||
| 520 | |a Purpose To evaluate the impact of the reduced life expectancy of patients (compared to a nonpatient group with the same age distribution) on their nominal risk of developing cancer from the diagnostic use of radiation. Method We define a “prognosis-based lifetime attributable risk modifier” (PROLARM) as the ratio of the risks for nonpatients and patients, a dimensionless quantity which indicates how strongly the life-time attributable risk (LAR) is reduced due to a patient’s prognosis. An approximation to this ratio can be given (named PROLARA) which depends only on the patient’s age at exposure and his/her life expectancy, but is independent of the exact choice of values for the baseline risk of cancer incidence and the excess relative risk (ERR) from radiation exposure. PROLARM and PROLARA were computed for a cohort of 4,285 female patients with metastatic breast cancer, for whom all necessary input data were available. Results LAR of solid cancer was significantly decreased in these patients: PROLARM >20 for age at exposure ≤65 years. For any reasonable choice of function for ERR, the approximation PROLARA gave a lower estimate of the reduction in risk. The risk for a patient from the above cohort, exposed at age 50 years, is decreased by a factor of 29 (PROLARM) and 27 (PROLARA). In other words, 50 mSv in a patient with metastatic breast cancer corresponds risk-wise to only 2 mSv in a nonpatient of the same age. Conclusion A major proportion of the total dose from diagnostic medical exposures does not constitute an additional cancer risk due to the poorer prognosis of patients compared to nonpatients of same gender and age. Our new PROLARA concept allows an estimation of the reduction in risk for any pathology when the associated survival is known. | ||
| 650 | 4 | |a Diagnostic radiation exposure |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Cancer risk |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Life-time attributable risk |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Prognosis-based life-time attributable risk modifier |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a PROLARA |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Schmidt, Matthias |4 aut | |
| 700 | 1 | |a Dietlein, Markus |4 aut | |
| 700 | 1 | |a Schicha, Harald |4 aut | |
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10.1007/s00259-009-1221-y doi (DE-627)SPR00313511X (SPR)s00259-009-1221-y-e DE-627 ger DE-627 rakwb eng Eschner, Wolfgang verfasserin aut PROLARA: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2009 Purpose To evaluate the impact of the reduced life expectancy of patients (compared to a nonpatient group with the same age distribution) on their nominal risk of developing cancer from the diagnostic use of radiation. Method We define a “prognosis-based lifetime attributable risk modifier” (PROLARM) as the ratio of the risks for nonpatients and patients, a dimensionless quantity which indicates how strongly the life-time attributable risk (LAR) is reduced due to a patient’s prognosis. An approximation to this ratio can be given (named PROLARA) which depends only on the patient’s age at exposure and his/her life expectancy, but is independent of the exact choice of values for the baseline risk of cancer incidence and the excess relative risk (ERR) from radiation exposure. PROLARM and PROLARA were computed for a cohort of 4,285 female patients with metastatic breast cancer, for whom all necessary input data were available. Results LAR of solid cancer was significantly decreased in these patients: PROLARM >20 for age at exposure ≤65 years. For any reasonable choice of function for ERR, the approximation PROLARA gave a lower estimate of the reduction in risk. The risk for a patient from the above cohort, exposed at age 50 years, is decreased by a factor of 29 (PROLARM) and 27 (PROLARA). In other words, 50 mSv in a patient with metastatic breast cancer corresponds risk-wise to only 2 mSv in a nonpatient of the same age. Conclusion A major proportion of the total dose from diagnostic medical exposures does not constitute an additional cancer risk due to the poorer prognosis of patients compared to nonpatients of same gender and age. Our new PROLARA concept allows an estimation of the reduction in risk for any pathology when the associated survival is known. Diagnostic radiation exposure (dpeaa)DE-He213 Cancer risk (dpeaa)DE-He213 Life-time attributable risk (dpeaa)DE-He213 Prognosis-based life-time attributable risk modifier (dpeaa)DE-He213 PROLARA (dpeaa)DE-He213 Schmidt, Matthias aut Dietlein, Markus aut Schicha, Harald aut Enthalten in European journal of nuclear medicine and molecular imaging Heidelberg [u.a.] : Springer-Verl., 2002 37(2009), 1 vom: 07. Aug. (DE-627)359787258 (DE-600)2098375-X 1619-7089 nnns volume:37 year:2009 number:1 day:07 month:08 https://dx.doi.org/10.1007/s00259-009-1221-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 37 2009 1 07 08 |
| spelling |
10.1007/s00259-009-1221-y doi (DE-627)SPR00313511X (SPR)s00259-009-1221-y-e DE-627 ger DE-627 rakwb eng Eschner, Wolfgang verfasserin aut PROLARA: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2009 Purpose To evaluate the impact of the reduced life expectancy of patients (compared to a nonpatient group with the same age distribution) on their nominal risk of developing cancer from the diagnostic use of radiation. Method We define a “prognosis-based lifetime attributable risk modifier” (PROLARM) as the ratio of the risks for nonpatients and patients, a dimensionless quantity which indicates how strongly the life-time attributable risk (LAR) is reduced due to a patient’s prognosis. An approximation to this ratio can be given (named PROLARA) which depends only on the patient’s age at exposure and his/her life expectancy, but is independent of the exact choice of values for the baseline risk of cancer incidence and the excess relative risk (ERR) from radiation exposure. PROLARM and PROLARA were computed for a cohort of 4,285 female patients with metastatic breast cancer, for whom all necessary input data were available. Results LAR of solid cancer was significantly decreased in these patients: PROLARM >20 for age at exposure ≤65 years. For any reasonable choice of function for ERR, the approximation PROLARA gave a lower estimate of the reduction in risk. The risk for a patient from the above cohort, exposed at age 50 years, is decreased by a factor of 29 (PROLARM) and 27 (PROLARA). In other words, 50 mSv in a patient with metastatic breast cancer corresponds risk-wise to only 2 mSv in a nonpatient of the same age. Conclusion A major proportion of the total dose from diagnostic medical exposures does not constitute an additional cancer risk due to the poorer prognosis of patients compared to nonpatients of same gender and age. Our new PROLARA concept allows an estimation of the reduction in risk for any pathology when the associated survival is known. Diagnostic radiation exposure (dpeaa)DE-He213 Cancer risk (dpeaa)DE-He213 Life-time attributable risk (dpeaa)DE-He213 Prognosis-based life-time attributable risk modifier (dpeaa)DE-He213 PROLARA (dpeaa)DE-He213 Schmidt, Matthias aut Dietlein, Markus aut Schicha, Harald aut Enthalten in European journal of nuclear medicine and molecular imaging Heidelberg [u.a.] : Springer-Verl., 2002 37(2009), 1 vom: 07. Aug. (DE-627)359787258 (DE-600)2098375-X 1619-7089 nnns volume:37 year:2009 number:1 day:07 month:08 https://dx.doi.org/10.1007/s00259-009-1221-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 37 2009 1 07 08 |
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10.1007/s00259-009-1221-y doi (DE-627)SPR00313511X (SPR)s00259-009-1221-y-e DE-627 ger DE-627 rakwb eng Eschner, Wolfgang verfasserin aut PROLARA: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2009 Purpose To evaluate the impact of the reduced life expectancy of patients (compared to a nonpatient group with the same age distribution) on their nominal risk of developing cancer from the diagnostic use of radiation. Method We define a “prognosis-based lifetime attributable risk modifier” (PROLARM) as the ratio of the risks for nonpatients and patients, a dimensionless quantity which indicates how strongly the life-time attributable risk (LAR) is reduced due to a patient’s prognosis. An approximation to this ratio can be given (named PROLARA) which depends only on the patient’s age at exposure and his/her life expectancy, but is independent of the exact choice of values for the baseline risk of cancer incidence and the excess relative risk (ERR) from radiation exposure. PROLARM and PROLARA were computed for a cohort of 4,285 female patients with metastatic breast cancer, for whom all necessary input data were available. Results LAR of solid cancer was significantly decreased in these patients: PROLARM >20 for age at exposure ≤65 years. For any reasonable choice of function for ERR, the approximation PROLARA gave a lower estimate of the reduction in risk. The risk for a patient from the above cohort, exposed at age 50 years, is decreased by a factor of 29 (PROLARM) and 27 (PROLARA). In other words, 50 mSv in a patient with metastatic breast cancer corresponds risk-wise to only 2 mSv in a nonpatient of the same age. Conclusion A major proportion of the total dose from diagnostic medical exposures does not constitute an additional cancer risk due to the poorer prognosis of patients compared to nonpatients of same gender and age. Our new PROLARA concept allows an estimation of the reduction in risk for any pathology when the associated survival is known. Diagnostic radiation exposure (dpeaa)DE-He213 Cancer risk (dpeaa)DE-He213 Life-time attributable risk (dpeaa)DE-He213 Prognosis-based life-time attributable risk modifier (dpeaa)DE-He213 PROLARA (dpeaa)DE-He213 Schmidt, Matthias aut Dietlein, Markus aut Schicha, Harald aut Enthalten in European journal of nuclear medicine and molecular imaging Heidelberg [u.a.] : Springer-Verl., 2002 37(2009), 1 vom: 07. Aug. (DE-627)359787258 (DE-600)2098375-X 1619-7089 nnns volume:37 year:2009 number:1 day:07 month:08 https://dx.doi.org/10.1007/s00259-009-1221-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 37 2009 1 07 08 |
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10.1007/s00259-009-1221-y doi (DE-627)SPR00313511X (SPR)s00259-009-1221-y-e DE-627 ger DE-627 rakwb eng Eschner, Wolfgang verfasserin aut PROLARA: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2009 Purpose To evaluate the impact of the reduced life expectancy of patients (compared to a nonpatient group with the same age distribution) on their nominal risk of developing cancer from the diagnostic use of radiation. Method We define a “prognosis-based lifetime attributable risk modifier” (PROLARM) as the ratio of the risks for nonpatients and patients, a dimensionless quantity which indicates how strongly the life-time attributable risk (LAR) is reduced due to a patient’s prognosis. An approximation to this ratio can be given (named PROLARA) which depends only on the patient’s age at exposure and his/her life expectancy, but is independent of the exact choice of values for the baseline risk of cancer incidence and the excess relative risk (ERR) from radiation exposure. PROLARM and PROLARA were computed for a cohort of 4,285 female patients with metastatic breast cancer, for whom all necessary input data were available. Results LAR of solid cancer was significantly decreased in these patients: PROLARM >20 for age at exposure ≤65 years. For any reasonable choice of function for ERR, the approximation PROLARA gave a lower estimate of the reduction in risk. The risk for a patient from the above cohort, exposed at age 50 years, is decreased by a factor of 29 (PROLARM) and 27 (PROLARA). In other words, 50 mSv in a patient with metastatic breast cancer corresponds risk-wise to only 2 mSv in a nonpatient of the same age. Conclusion A major proportion of the total dose from diagnostic medical exposures does not constitute an additional cancer risk due to the poorer prognosis of patients compared to nonpatients of same gender and age. Our new PROLARA concept allows an estimation of the reduction in risk for any pathology when the associated survival is known. Diagnostic radiation exposure (dpeaa)DE-He213 Cancer risk (dpeaa)DE-He213 Life-time attributable risk (dpeaa)DE-He213 Prognosis-based life-time attributable risk modifier (dpeaa)DE-He213 PROLARA (dpeaa)DE-He213 Schmidt, Matthias aut Dietlein, Markus aut Schicha, Harald aut Enthalten in European journal of nuclear medicine and molecular imaging Heidelberg [u.a.] : Springer-Verl., 2002 37(2009), 1 vom: 07. Aug. (DE-627)359787258 (DE-600)2098375-X 1619-7089 nnns volume:37 year:2009 number:1 day:07 month:08 https://dx.doi.org/10.1007/s00259-009-1221-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 37 2009 1 07 08 |
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10.1007/s00259-009-1221-y doi (DE-627)SPR00313511X (SPR)s00259-009-1221-y-e DE-627 ger DE-627 rakwb eng Eschner, Wolfgang verfasserin aut PROLARA: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2009 Purpose To evaluate the impact of the reduced life expectancy of patients (compared to a nonpatient group with the same age distribution) on their nominal risk of developing cancer from the diagnostic use of radiation. Method We define a “prognosis-based lifetime attributable risk modifier” (PROLARM) as the ratio of the risks for nonpatients and patients, a dimensionless quantity which indicates how strongly the life-time attributable risk (LAR) is reduced due to a patient’s prognosis. An approximation to this ratio can be given (named PROLARA) which depends only on the patient’s age at exposure and his/her life expectancy, but is independent of the exact choice of values for the baseline risk of cancer incidence and the excess relative risk (ERR) from radiation exposure. PROLARM and PROLARA were computed for a cohort of 4,285 female patients with metastatic breast cancer, for whom all necessary input data were available. Results LAR of solid cancer was significantly decreased in these patients: PROLARM >20 for age at exposure ≤65 years. For any reasonable choice of function for ERR, the approximation PROLARA gave a lower estimate of the reduction in risk. The risk for a patient from the above cohort, exposed at age 50 years, is decreased by a factor of 29 (PROLARM) and 27 (PROLARA). In other words, 50 mSv in a patient with metastatic breast cancer corresponds risk-wise to only 2 mSv in a nonpatient of the same age. Conclusion A major proportion of the total dose from diagnostic medical exposures does not constitute an additional cancer risk due to the poorer prognosis of patients compared to nonpatients of same gender and age. Our new PROLARA concept allows an estimation of the reduction in risk for any pathology when the associated survival is known. Diagnostic radiation exposure (dpeaa)DE-He213 Cancer risk (dpeaa)DE-He213 Life-time attributable risk (dpeaa)DE-He213 Prognosis-based life-time attributable risk modifier (dpeaa)DE-He213 PROLARA (dpeaa)DE-He213 Schmidt, Matthias aut Dietlein, Markus aut Schicha, Harald aut Enthalten in European journal of nuclear medicine and molecular imaging Heidelberg [u.a.] : Springer-Verl., 2002 37(2009), 1 vom: 07. Aug. (DE-627)359787258 (DE-600)2098375-X 1619-7089 nnns volume:37 year:2009 number:1 day:07 month:08 https://dx.doi.org/10.1007/s00259-009-1221-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 37 2009 1 07 08 |
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Enthalten in European journal of nuclear medicine and molecular imaging 37(2009), 1 vom: 07. Aug. volume:37 year:2009 number:1 day:07 month:08 |
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Enthalten in European journal of nuclear medicine and molecular imaging 37(2009), 1 vom: 07. Aug. volume:37 year:2009 number:1 day:07 month:08 |
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European journal of nuclear medicine and molecular imaging |
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Eschner, Wolfgang @@aut@@ Schmidt, Matthias @@aut@@ Dietlein, Markus @@aut@@ Schicha, Harald @@aut@@ |
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Method We define a “prognosis-based lifetime attributable risk modifier” (PROLARM) as the ratio of the risks for nonpatients and patients, a dimensionless quantity which indicates how strongly the life-time attributable risk (LAR) is reduced due to a patient’s prognosis. An approximation to this ratio can be given (named PROLARA) which depends only on the patient’s age at exposure and his/her life expectancy, but is independent of the exact choice of values for the baseline risk of cancer incidence and the excess relative risk (ERR) from radiation exposure. PROLARM and PROLARA were computed for a cohort of 4,285 female patients with metastatic breast cancer, for whom all necessary input data were available. Results LAR of solid cancer was significantly decreased in these patients: PROLARM >20 for age at exposure ≤65 years. For any reasonable choice of function for ERR, the approximation PROLARA gave a lower estimate of the reduction in risk. The risk for a patient from the above cohort, exposed at age 50 years, is decreased by a factor of 29 (PROLARM) and 27 (PROLARA). In other words, 50 mSv in a patient with metastatic breast cancer corresponds risk-wise to only 2 mSv in a nonpatient of the same age. Conclusion A major proportion of the total dose from diagnostic medical exposures does not constitute an additional cancer risk due to the poorer prognosis of patients compared to nonpatients of same gender and age. 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Eschner, Wolfgang |
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Eschner, Wolfgang misc Diagnostic radiation exposure misc Cancer risk misc Life-time attributable risk misc Prognosis-based life-time attributable risk modifier misc PROLARA PROLARA: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure |
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PROLARA: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure Diagnostic radiation exposure (dpeaa)DE-He213 Cancer risk (dpeaa)DE-He213 Life-time attributable risk (dpeaa)DE-He213 Prognosis-based life-time attributable risk modifier (dpeaa)DE-He213 PROLARA (dpeaa)DE-He213 |
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misc Diagnostic radiation exposure misc Cancer risk misc Life-time attributable risk misc Prognosis-based life-time attributable risk modifier misc PROLARA |
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misc Diagnostic radiation exposure misc Cancer risk misc Life-time attributable risk misc Prognosis-based life-time attributable risk modifier misc PROLARA |
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misc Diagnostic radiation exposure misc Cancer risk misc Life-time attributable risk misc Prognosis-based life-time attributable risk modifier misc PROLARA |
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PROLARA: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure |
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prolara: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure |
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PROLARA: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure |
| abstract |
Purpose To evaluate the impact of the reduced life expectancy of patients (compared to a nonpatient group with the same age distribution) on their nominal risk of developing cancer from the diagnostic use of radiation. Method We define a “prognosis-based lifetime attributable risk modifier” (PROLARM) as the ratio of the risks for nonpatients and patients, a dimensionless quantity which indicates how strongly the life-time attributable risk (LAR) is reduced due to a patient’s prognosis. An approximation to this ratio can be given (named PROLARA) which depends only on the patient’s age at exposure and his/her life expectancy, but is independent of the exact choice of values for the baseline risk of cancer incidence and the excess relative risk (ERR) from radiation exposure. PROLARM and PROLARA were computed for a cohort of 4,285 female patients with metastatic breast cancer, for whom all necessary input data were available. Results LAR of solid cancer was significantly decreased in these patients: PROLARM >20 for age at exposure ≤65 years. For any reasonable choice of function for ERR, the approximation PROLARA gave a lower estimate of the reduction in risk. The risk for a patient from the above cohort, exposed at age 50 years, is decreased by a factor of 29 (PROLARM) and 27 (PROLARA). In other words, 50 mSv in a patient with metastatic breast cancer corresponds risk-wise to only 2 mSv in a nonpatient of the same age. Conclusion A major proportion of the total dose from diagnostic medical exposures does not constitute an additional cancer risk due to the poorer prognosis of patients compared to nonpatients of same gender and age. Our new PROLARA concept allows an estimation of the reduction in risk for any pathology when the associated survival is known. © Springer-Verlag 2009 |
| abstractGer |
Purpose To evaluate the impact of the reduced life expectancy of patients (compared to a nonpatient group with the same age distribution) on their nominal risk of developing cancer from the diagnostic use of radiation. Method We define a “prognosis-based lifetime attributable risk modifier” (PROLARM) as the ratio of the risks for nonpatients and patients, a dimensionless quantity which indicates how strongly the life-time attributable risk (LAR) is reduced due to a patient’s prognosis. An approximation to this ratio can be given (named PROLARA) which depends only on the patient’s age at exposure and his/her life expectancy, but is independent of the exact choice of values for the baseline risk of cancer incidence and the excess relative risk (ERR) from radiation exposure. PROLARM and PROLARA were computed for a cohort of 4,285 female patients with metastatic breast cancer, for whom all necessary input data were available. Results LAR of solid cancer was significantly decreased in these patients: PROLARM >20 for age at exposure ≤65 years. For any reasonable choice of function for ERR, the approximation PROLARA gave a lower estimate of the reduction in risk. The risk for a patient from the above cohort, exposed at age 50 years, is decreased by a factor of 29 (PROLARM) and 27 (PROLARA). In other words, 50 mSv in a patient with metastatic breast cancer corresponds risk-wise to only 2 mSv in a nonpatient of the same age. Conclusion A major proportion of the total dose from diagnostic medical exposures does not constitute an additional cancer risk due to the poorer prognosis of patients compared to nonpatients of same gender and age. Our new PROLARA concept allows an estimation of the reduction in risk for any pathology when the associated survival is known. © Springer-Verlag 2009 |
| abstract_unstemmed |
Purpose To evaluate the impact of the reduced life expectancy of patients (compared to a nonpatient group with the same age distribution) on their nominal risk of developing cancer from the diagnostic use of radiation. Method We define a “prognosis-based lifetime attributable risk modifier” (PROLARM) as the ratio of the risks for nonpatients and patients, a dimensionless quantity which indicates how strongly the life-time attributable risk (LAR) is reduced due to a patient’s prognosis. An approximation to this ratio can be given (named PROLARA) which depends only on the patient’s age at exposure and his/her life expectancy, but is independent of the exact choice of values for the baseline risk of cancer incidence and the excess relative risk (ERR) from radiation exposure. PROLARM and PROLARA were computed for a cohort of 4,285 female patients with metastatic breast cancer, for whom all necessary input data were available. Results LAR of solid cancer was significantly decreased in these patients: PROLARM >20 for age at exposure ≤65 years. For any reasonable choice of function for ERR, the approximation PROLARA gave a lower estimate of the reduction in risk. The risk for a patient from the above cohort, exposed at age 50 years, is decreased by a factor of 29 (PROLARM) and 27 (PROLARA). In other words, 50 mSv in a patient with metastatic breast cancer corresponds risk-wise to only 2 mSv in a nonpatient of the same age. Conclusion A major proportion of the total dose from diagnostic medical exposures does not constitute an additional cancer risk due to the poorer prognosis of patients compared to nonpatients of same gender and age. Our new PROLARA concept allows an estimation of the reduction in risk for any pathology when the associated survival is known. © Springer-Verlag 2009 |
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PROLARA: prognosis-based lifetime attributable risk approximation for cancer from diagnostic radiation exposure |
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https://dx.doi.org/10.1007/s00259-009-1221-y |
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Schmidt, Matthias Dietlein, Markus Schicha, Harald |
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10.1007/s00259-009-1221-y |
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2024-07-03T17:31:45.577Z |
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| score |
7.3993816 |