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Citation List for SAOP Tools

CRASH score

Original article: Cancer 2012[1]

Studies using CRASH score: NCT02904031[2]

SIOG 2013 poster Limoges

John Snowden, UKALL 60

Comment: S. Cousin, Journal d’OncoGériatrie, 3(5), 2012, p.247.

Luciani et al., ASCO 2015[3] http://abstracts.asco.org/156/AbstView_156_150632.html

Fargeas et al., SIOG 2014[4]

Fargeas et al., SIOG 2015

P048

CRASH SCORE IN THE OLDER FRENCH NON HODGKIN

LYMPHOMA RECEIVING CHEMOTHERAPY, FINAL RESULTS

  1. B. Fargeas 1,*, N. Signol 1, A. Penot 1, J. Abraham 1, A. Olivrie 1,M.-A. Picat 2, A. Jaccard 1, D. Bordessoule 1

1Service d’Hématologie Clinique et Thérapie Cellulaire, 2Service de Gériatrie, CHU Limoges, Limoges, France

Introduction: Non-Hodgkin lymphoma (NHL), are one of the most frequent hematological malignancy observed in elderly patients (pts). Comprehensive geriatric assessment (CGA) is the best way to identify functional problems or disabilities of these pts. NHL vary considerably in terms of performance status, functional reseve and comorbidities. The chemosensivity of NHL leads to prescription of a toxic anthracycline chemotherapy with rituximab for fit B NHL and adapted chemo with rituximab for the other. Pts have different level of vulnerability to chemotherapy toxicity. CRASH Score (CS) is known to be useful in older patients for screening risk of severe chemotoxicity in some variety of cancer and in NHL.

Objectives: Validate by a prospective use in daily routine, the predictive value of adverse event of CS in a geriatric population of NHL receiving chemotherapy regimen.

Methods: Prospective study on all consecutive NHL pts, treated by chemotherapy from September 2013 to June 2015. Inclusion criteria: 1) 70 years and older pts 2) histologically proved diagnosis of NHL according to the guideline of OMS 3) first line and relapse regimen 4) geriatric assessment according to the SIOG recommendations for CGA. Therapy has been chosen in a collaborative multidisciplinary team according national guidelines and care has been organized in the multicentric regional network. We calculated CS before the chemo and collected all events, grade 3 or over, according to NCI-Common Terminology Criteria for Adverse Events version 3.0 or geriatrics health problems, up to one month following first cure. CRASH points for Toxicity of chemotherapy regimen were established using the chemotox table values and regimens not listed were scored by analogy.

Results: 85/87 included pts evaluable (excluded from the analysis 2 pts: missing data), mean age 79 years (70-91 years), 58% (49/85) older than 80 years. Sex ratio 0.98. Histological subtypes: DLBCL 42% (36), follicular lymphoma 17% (14), mantle cells lymphoma 15% (13), others 26% (22). Chemotherapy were anthracycline 40% (34): ZEM 20% (17), mini CHOP 18% (16), GVD 2% (1) or non anthracycline regimen 60% (51): bendamustine 10% (9), VP16-Holoxan 12% (10), COPAracytine 13% (11), others 24% (21). 90% (77) pts received rituximab. CRASH score: Low or Intlow in 39% pts (33), Int-high or High in 61% pts (52). Hematologic risk factor: Low or Int-low in 33% (28) pts, Int-high or High in 67% (57) pts. Non hematologic risk factor: Low or Int-low in 52% (44) pts, Int-high or High in 48% (41) pts. Severe toxicity (grade 3 and over or severe geriatrics problems) was observed in 32% (27) pts. Among pts with Low or Med-Low, n=33 (39%), adverse events have been observed in 10% (n=3) and significantly higher in 46% (n=24)

in pts with High or Med-high, n=52 (61%) (p=0.0003). Conclusion: This data collected until June 2015 confirm preliminary results presented in SIOG 2014 and highlighted the good predictive value for adverse events of CS. These tool  objectives that quite half pts with High or Int-high have serious adverse events. For most frail pts management is adapted to  their real health status. The next step of this study is to organize  proactive care organization for all patients with High or Int-high CS eligible to chemotherapy. It will be a personalized follow-up with a nurse care manager, free direct incall for patients and weekly call by nurse, collaborative management with general practitioner. Then, we will search the impact of this management on adverse event occurrence.

Disclosure of interest: None declared 

Keywords: Lymphoma, network

P096

ESTIMATING HEMATOLOGIC CHEMOTHERAPY RISK OF

TOXICITY IN ELDERLY TREATED PATIENTS IN CATHOLIC

UNIVERSITY OF CHILE CANCER CENTER

  1. Calderon 1,*, V. Rojas 2, G. Fasce 1, M. Carrasco 2, M. Herrera 2,
  2. Nervi 2, F. Scheel 2

1FALP, 2Universidad Católica de Chile, Santiago, Chile

Introduction: Elderly have particularities that make therapeutic decisions difficult. They are a heterogeneous and complex population, with multiple comorbidities, geriatric syndromes and various states of functional decline. These characteristics affect life expectancy and determine a frailty phenotype, which heightens the risk of adverse events such as chemotherapy toxicity. Two different groups have developed scales to predict chemotherapy toxicity risk in elderly (CRASH and CARG). None of these have been validated in Chile.

Objectives: The purpose of this study was to check the predictive capacity of these instruments to determine the hematologic chemotherapy risk in elderly adults over 65 years of age in our country.

Methods: Between April 2012 and April 2014, patients over 65 years of age with hematologic tumors were included in Catholic University of Chile Cancer Center. Before treatment was initiated patients were evaluated by a geriatrician who applied both instruments. After the end of the study, medical charts were reviewed looking for Grade 3, 4 or 5 hematologic toxicity during treatment.

Results: Eighty five patients were included, 59% were women, age average was 75 years (65-91). Most prevalent diagnosis where digestive system neoplasms (GI) (54.2%), breast (14.3%), and urogyn (UG) (14.3%). Ninety four percent were ECOG 0-1. Twenty eight percent developed hematologic toxicity. When scales were checked, the predictors with higher correlations were: combined chemotherapy (p=0.033), GI or UG p=0.036), and anemia (p=0.01). Patients with higher CARG scores had more risk of toxicity than those with lower scores. CRASH scale did not show statistical significant correlations.

Conclusion: CRASH score did not predicted hematologic toxicity risk in our sample. Higher CARG scores did related with higher risks of toxicity. It would be recommended to validate these data with other populations and bigger samples.

Disclosure of interest: None declared

Keywords: Chemotherapy, risk of toxicity, elderly

 

MAX2

Original: [5, 6]

CRASH score[1]

Janssen-Heijnen et al, CROH 2011[7]

Hoppe et al. JCO 2013[8http://jco.ascopubs.org/content/31/31/3877.full.pdf+html

Shin et al. JGO 2012 [9]

Extermann, Cancer 2015[10]

Luciani et al, JGO 2015[11]

Lee et al., JGO 2017[12]

Kim et al. JGO 2019[13]

 

SAOP2

Original : Extermann M.[14]
Comparison with G8: Russo et al.[15]

Gretchen Kimmick1, Rebecca Shelby2, Jessica Robertson1, Bailey Maloney3, Claudia Meyer4, Ravi Kanesvaran5, and Heidi White6. Detecting geriatric needs in older breast cancer patients through use of a brief screener. AGS 2015 meeting.

Amber Meurer et al., P086, SIOG 2015.

References

  1. Extermann, M., et al., Predicting the risk of chemotherapy toxicity in older patients: the Chemotherapy Risk Assessment Scale for High-Age Patients (CRASH) score. Cancer, 2012. 118(13): p. 3377-86.
  2. Battaglin, F., et al., The PANDA study: a randomized phase II study of first-line FOLFOX plus panitumumab versus 5FU plus panitumumab in RAS and BRAF wild-type elderly metastatic colorectal cancer patients. BMC Cancer, 2018. 18(1): p. 98.
  3. Luciani A, B.A., Battisti N, Romanato G, Caldiera S, Bergamo F, Roma A, Zagonel V, Foa P, The assessment of chemotherapy risk in elderly cancer patients: Validation of the CRASH score in an Italian cohort. J Clin Oncol, 2015. 33(suppl): p. e20521.
  4. Fargeas, J., Penot A, Olivrie A, Picat M-A, Touati M, Signol N, Jaccard A, Bordessoule D., Crash score in the older French non-Hodgkin lymphoma receiving chemotherapy, first results. J Geriatr Oncol, 2014. 5(Suppl 2): p. S12-S13.
  5. Extermann, M., et al., MAX2--a convenient index to estimate the average per patient risk for chemotherapy toxicity; validation in ECOG trials. Eur J Cancer, 2004. 40(8): p. 1193-8.
  6. Extermann, M., et al., Predictors of tolerance to chemotherapy in older cancer patients: a prospective pilot study. Eur J Cancer, 2002. 38(11): p. 1466-73.
  7. Janssen-Heijnen, M.L., M. Extermann, and I.E. Boler, Can first cycle CBCs predict older patients at very low risk of neutropenia during further chemotherapy? Critical reviews in oncology/hematology, 2011. 79(1): p. 43-50.
  8. Hoppe, S., et al., Functional decline in older patients with cancer receiving first-line chemotherapy. J Clin Oncol, 2013. 31(31): p. 3877-82.
  9. Shin, D.Y., et al., Toxicities and functional consequences of systemic chemotherapy in elderly Korean patients with cancer: A prospective cohort study using Comprehensive Geriatric Assessment. Journal of Geriatric Oncology, 2012. 3(4): p. 359-367.
  10. Extermann, M., R.R. Reich, and M. Sehovic, Chemotoxicity recurrence in older patients: Risk factors and effectiveness of preventive strategies-a prospective study. Cancer, 2015. 121(17): p. 2984-92.
  11. Luciani, A., et al., Estimating the risk of chemotherapy toxicity in older patients with cancer: The role of the Vulnerable Elders Survey-13 (VES-13). J Geriatr Oncol, 2015. 6(4): p. 272-9.
  12. Lee, J.J., et al., Using heat maps to assess the multidimensional association of comorbidities with survival in older cancer patients treated with chemotherapy. J Geriatr Oncol, 2017. 8(5): p. 336-342.
  13. Kim, K.H., et al., Association of multidimensional comorbidities with survival, toxicity, and unplanned hospitalizations in older adults with metastatic colorectal cancer treated with chemotherapy. J Geriatr Oncol, 2019.
  14. Extermann, M., Evaluation of the Senior Cancer Patient: Comprehensive Geriatric Assessment and Screening Tools for the Elderly, in Handbook of Cancer in the Senior Patient, D. Schrijvers, Aapro M, Zakotnik B, Audisio R, van Halteren H, Hurria A., Editor. 2010, Informa Healthcare: New York, London. p. 13-21.
  15. Russo, C., et al., Predictive values of two frailty screening tools in older patients with solid cancer: a comparison of SAOP2 and G8. Oncotarget, 2018. 9(80): p. 35056-35068.