Clinical trial NCT03434561: Comparing Different Methods for Collection of Comorbidity Data Per the HCT-CI
Official title: Comparing Different Methods for Collection of Comorbidity Data Per the Hematopoietic Cell Transplantation Comorbidity Index (HCT-CI)
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Hematopoietic Malignancy
Keywords: hematopoietic stem cell transplantation
Lead sponsor: Fred Hutchinson Cancer Center
Sponsor class: OTHER
Collaborators: name: National Heart, Lung, and Blood Institute (NHLBI)
First posted: 2018-02-15
Enrollment: 360
Sex: ALL
Minimum age (years): 20
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients diagnosed with hematological malignancies who are being treated with allogeneic hematopoietic cell transplantation (HCT) at the Seattle Cancer Care Alliance

Brief summary: Comorbidity assessment in the field of HCT might be a burden on the medical team at the clinic or the research staff. This research study aims to explore and validate new methods, Claims-based and patient questionnaire-based, as alternatives to the standard chart-based method in order to facilitate comorbidity coding. The study aims to save time and effort of medical personnel and to ensure the inclusion of comorbidity information in all clinical trials and outcome research studies in order to improve the accuracy of treatment decision-making, patient assignment to appropriate HCT strategy and hence HCT outcomes.

Detailed description: Studies have shown the importance of pre-transplant comorbidities in predicting mortality after allogeneic HCT.

However, comorbidity assessment might be a burden on the medical team at the clinic or the research staff. This research study aims to explore and validate new methods as alternatives to the standard chart-based method in order to facilitate comorbidity coding. The study aims to save time and effort of medical personnel and to ensure the inclusion of comorbidity information in all clinical trials and outcome research studies in order to improve the accuracy of treatment decision-making, patient assignment to appropriate HCT strategy and hence HCT outcomes.

This study will investigate two parallel approaches aimed at simplifying comorbidity assessment and thereby facilitating wide-spread use of the HCT-CI. Patient questionnaire-based and Claims-based methods will be tested as possible alternative to the Chart-based method. primary outcome is prediction of non-relapse mortality. It is expected that once this method of comorbidity coding is validated, it will benefit physicians in non-academic institutions and community clinics.

Eligibility criteria: Inclusion Criteria:

* Patients eligible for autologous or allogeneic HCT.
* Able to speak and read English.
* Willing and able to provide informed consent.
* There is no restriction based on diagnosis, intensity of conditioning regimen, type of donor graft, degree of HLA-matching, or stem cell source.
* Patients \>20 years old
* Access to a telephone for study-related communications.

Exclusion Criteria:

* HCT candidates who cannot read, write, or speak English.
* Patients \<20 years old

Primary outcomes:
measure: Compare the rate of agreement on HCT-CI scores between 3 measures
timeFrame: 2 years
Secondary outcomes:
measure: Assess the accuracy of predicting HCT outcomes and resource utilization (e.g., hospitalization) between the three methods of scoring
timeFrame: 2 years
Other outcomes:
Locations:
city: Seattle
country: United States
facility: Fred Hutchinson Cancer Research Center
state: Washington
Study officials:
affiliation: Associate Member, Fred Hutch
name: Mohamed Sorror, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Sorror ML, Maris MB, Storer B, Sandmaier BM, Diaconescu R, Flowers C, Maloney DG, Storb R. Comparing morbidity and mortality of HLA-matched unrelated donor hematopoietic cell transplantation after nonmyeloablative and myeloablative conditioning: influence of pretransplantation comorbidities. Blood. 2004 Aug 15;104(4):961-8. doi: 10.1182/blood-2004-02-0545. Epub 2004 Apr 27.
citation: Diaconescu R, Flowers CR, Storer B, Sorror ML, Maris MB, Maloney DG, Sandmaier BM, Storb R. Morbidity and mortality with nonmyeloablative compared with myeloablative conditioning before hematopoietic cell transplantation from HLA-matched related donors. Blood. 2004 Sep 1;104(5):1550-8. doi: 10.1182/blood-2004-03-0804. Epub 2004 May 18.
citation: Piccirillo JF, Vlahiotis A, Barrett LB, Flood KL, Spitznagel EL, Steyerberg EW. The changing prevalence of comorbidity across the age spectrum. Crit Rev Oncol Hematol. 2008 Aug;67(2):124-32. doi: 10.1016/j.critrevonc.2008.01.013. Epub 2008 Mar 28.
citation: Gloeckler Ries LA, Reichman ME, Lewis DR, Hankey BF, Edwards BK. Cancer survival and incidence from the Surveillance, Epidemiology, and End Results (SEER) program. Oncologist. 2003;8(6):541-52. doi: 10.1634/theoncologist.8-6-541.
citation: McClune BL, Weisdorf DJ, Pedersen TL, Tunes da Silva G, Tallman MS, Sierra J, Dipersio J, Keating A, Gale RP, George B, Gupta V, Hahn T, Isola L, Jagasia M, Lazarus H, Marks D, Maziarz R, Waller EK, Bredeson C, Giralt S. Effect of age on outcome of reduced-intensity hematopoietic cell transplantation for older patients with acute myeloid leukemia in first complete remission or with myelodysplastic syndrome. J Clin Oncol. 2010 Apr 10;28(11):1878-87. doi: 10.1200/JCO.2009.25.4821. Epub 2010 Mar 8.
citation: van Spronsen DJ, Janssen-Heijnen ML, Lemmens VE, Peters WG, Coebergh JW. Independent prognostic effect of co-morbidity in lymphoma patients: results of the population-based Eindhoven Cancer Registry. Eur J Cancer. 2005 May;41(7):1051-7. doi: 10.1016/j.ejca.2005.01.010.
citation: Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-83. doi: 10.1016/0021-9681(87)90171-8.
citation: Di Iorio B, Cillo N, Cirillo M, De Santo NG. Charlson Comorbidity Index is a predictor of outcomes in incident hemodialysis patients and correlates with phase angle and hospitalization. Int J Artif Organs. 2004 Apr;27(4):330-6. doi: 10.1177/039139880402700409.
citation: Goldstein LB, Samsa GP, Matchar DB, Horner RD. Charlson Index comorbidity adjustment for ischemic stroke outcome studies. Stroke. 2004 Aug;35(8):1941-5. doi: 10.1161/01.STR.0000135225.80898.1c. Epub 2004 Jul 1.
citation: Hemmelgarn BR, Manns BJ, Quan H, Ghali WA. Adapting the Charlson Comorbidity Index for use in patients with ESRD. Am J Kidney Dis. 2003 Jul;42(1):125-32. doi: 10.1016/s0272-6386(03)00415-3.
citation: Sachdev M, Sun JL, Tsiatis AA, Nelson CL, Mark DB, Jollis JG. The prognostic importance of comorbidity for mortality in patients with stable coronary artery disease. J Am Coll Cardiol. 2004 Feb 18;43(4):576-82. doi: 10.1016/j.jacc.2003.10.031.
citation: Lubke T, Monig SP, Schneider PM, Holscher AH, Bollschweiler E. [Does Charlson-comorbidity index correlate with short-term outcome in patients with gastric cancer?]. Zentralbl Chir. 2003 Nov;128(11):970-6. doi: 10.1055/s-2003-44805. German.
citation: Firat S, Byhardt RW, Gore E. Comorbidity and Karnofksy performance score are independent prognostic factors in stage III non-small-cell lung cancer: an institutional analysis of patients treated on four RTOG studies. Radiation Therapy Oncology Group. Int J Radiat Oncol Biol Phys. 2002 Oct 1;54(2):357-64. doi: 10.1016/s0360-3016(02)02939-5.
citation: Sabin SL, Rosenfeld RM, Sundaram K, Har-el G, Lucente FE. The impact of comorbidity and age on survival with laryngeal cancer. Ear Nose Throat J. 1999 Aug;78(8):578, 581-4.
citation: Singh B, Bhaya M, Stern J, Roland JT, Zimbler M, Rosenfeld RM, Har-El G, Lucente FE. Validation of the Charlson comorbidity index in patients with head and neck cancer: a multi-institutional study. Laryngoscope. 1997 Nov;107(11 Pt 1):1469-75. doi: 10.1097/00005537-199711000-00009.
citation: Extermann M. Measuring comorbidity in older cancer patients. Eur J Cancer. 2000 Mar;36(4):453-71. doi: 10.1016/s0959-8049(99)00319-6.
citation: Katz JN, Chang LC, Sangha O, Fossel AH, Bates DW. Can comorbidity be measured by questionnaire rather than medical record review? Med Care. 1996 Jan;34(1):73-84. doi: 10.1097/00005650-199601000-00006.
citation: Corser W, Sikorskii A, Olomu A, Stommel M, Proden C, Holmes-Rovner M. "Concordance between comorbidity data from patient self-report interviews and medical record documentation". BMC Health Serv Res. 2008 Apr 16;8:85. doi: 10.1186/1472-6963-8-85.
citation: Sorror ML, Maris MB, Storb R, Baron F, Sandmaier BM, Maloney DG, Storer B. Hematopoietic cell transplantation (HCT)-specific comorbidity index: a new tool for risk assessment before allogeneic HCT. Blood. 2005 Oct 15;106(8):2912-9. doi: 10.1182/blood-2005-05-2004. Epub 2005 Jun 30.
citation: Bacigalupo A, Ballen K, Rizzo D, Giralt S, Lazarus H, Ho V, Apperley J, Slavin S, Pasquini M, Sandmaier BM, Barrett J, Blaise D, Lowski R, Horowitz M. Defining the intensity of conditioning regimens: working definitions. Biol Blood Marrow Transplant. 2009 Dec;15(12):1628-33. doi: 10.1016/j.bbmt.2009.07.004. Epub 2009 Sep 1.