Abstract
Many cutpoints have been proposed to categorize continuous variables in childhood acute lymphoblastic leukaemia (white blood cell count, peripheral blast cell count, haemoglobin level, platelet count and age), and have been used to define therapeutic subgroups. This variation in the choice of cutpoints leads to a bias called the ‘Will Rogers phenomenon'. The aim of this study was to analyse variations in the relative risk of relapse or death as a function of continuous prognostic variables in childhood ALL and to discuss the choice of cutpoints. We studied a population of 1545 children with ALL enrolled in three consecutive protocols named FRALLE 83, FRALLE 87 and FRALLE 89. We estimated the risk of relapse or death associated with different values of each continuous prognostic variable by dividing the sample into quintiles of the distribution of the variables. As regards age, a category of children under 1 year of age was distinguished and the rest of the population was divided into quintiles. The floated variance method was used to calculate the confidence interval of each relative risk, including the reference category. The relation between the quantitative prognostic factors and the risk was monotonic for each variable, except for age. For the white blood cell count (WBC), the relation is log linear. The risk associated with WBC values in the upper quintile was 1.9 times higher than that in the lower quintile. The peripheral blast cell count correlated strongly with WBC (correlation coefficient: 0.99). The risk increased with the haemoglobin level, and the risk in the upper quintile was 1.3 times higher than that in the lower quintile. The risk decreased as the platelet count increased: the risk in the lower quintile was 1.2 times higher than that in the upper quintile. The risk increased gradually with increasing age above one year. The small subgroup of patients (2.5% of the population) under 1 year of age at diagnosis had a risk 2.6 times higher than the reference category of patients between 3 and 4.3 years of age. When the risk associated with a quantitative prognostic factor varies monotonously, the selection of a cutpoint is arbitrary and represents a loss of information. Despite this loss of information, such arbitrary categorization may be necessary to define therapeutic stratification. In that case, consensus cutpoints must be defined if one wants to avoid the Will Rogers phenomenon. The cutpoints proposed by the Rome workshop and the NCI are arbitrary, but may represent an acceptable convention. © 2000 Cancer Research Campaign http://www.bjcancer.com
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References
Altman DG, Lausen B, Sauerbrei W and Schumacher M (1994) Danger of using “optimal” cutpoints in the evaluation of prognostic factors. J Natl Cancer Inst 86: 829–835
Bleyer WA (1989) Remaining problems in the staging and treatment of childhood lymphoblastic leukemia. Am J Pediatr Hematol Oncol 11: 371–379
Bleyer WA, Sather H, Coccia P, Lukens J, Siegel S and Hammond GD (1986) The staging of childhood acute lymphoblastic leukemia: strategies of the Childrens Cancer Study Group and a three-dimensional technic of multivariate analysis. Med Pediatr Oncol 14: 271–280
Bucsky P, Reiter A, Ritter J, Dopfer R and Riehm H (1988) Die akute lymphoblastiche leukämie im Säuglingsalter: Eregebnissse aus fünf multisentrischen therapiestudien ALL-BFM 1970–1986. Klin Pädiatr 200: 177–183
Chessells JM, Bailey C and Richards SM (1995) Intensification of treatment and survival in all children with lymphoblastic leukaemia: results of UK medical research council UKALL X. Lancet 345: 143–148
Collet D (1994) Modelling survival data in medical research. Chapman and Hall: London
Cox DR (1972) Regression models and life tables (with discussion). J R Stat Soc 34: 248–275
Donadieu J, Auclerc MF, Baruchel A, Leblanc T, Landman-Parker J, Perel Y, Michel G, Cornu G, Bordigoni P, Sommelet D, Leverger G, Hill C and Schaison G (1998) Critical study of prognostic factors in childhood acute lymphoblastic leukaemia: differences in outcome are poorly explained by the most significant prognostic variables. Br J Haematol 102: 729–739
Easton DF, Peto J and Babiker AGAG (1991) Floating absolute risk: an alternative to relative risk in survival and case control analysis avoiding an arbitrary reference group. Stat Med 10: 1025–1035
Feinstein AR, Sosin DM and Wells CK (1985) The Will Rogers phenomenon: Stage migration and new diagnosis techniques as a source of misleading statistics for survival in cancer. N Engl J Med 312: 1604–1608
Gustafsson G, Kreuger A, Clausen N, Garwicz S, Kristinsson J, Lie SO, Moe PJ, Perkkio M, Yssing M and Saarinen-Pihkala UM (1998) Intensified treatment of acute childhood lymphoblastic leukaemia has improved prognosis, especially in non-high-risk patients: the Nordic experience of 2648 patients diagnosed between 1981 and 1996. Nordic Society of Paediatric Haematology and Oncology. Acta Paediatrica 87: 1151–1161
Hill C (1993) Valeur pronostique d'une variable continue et point de césure optimal. Bull Cancer 80: 649–652
Hilsenbeck SM, Clark GM and McGuire WL (1992) Why do so many prognostic factors fail to pan out?. Breast Cancer Res Treat 22: 197–206
Hiyoshi Y, Fujimoto T, Kuriya N, Otani Y, Ibu K, Yanai M, Sasaki K, Shingaki Y and Yokoyama T S-K (1985) Prognostic factors in children with acute lymphoblastic leukemia. Part II: multivariate analysis. Jpn J Clin Oncol 15: 13–23
Jacquillat C, Weil M, Auclerc MF, Chastang C, Flandrin G, Izrael V, Schaison G, Degos L, Boiron M and Bernard J (1978) Prognosis and treatment of acute lymphoblastic leukemia. Cancer Chemother Pharmacol 1: 113–122
Mastrangelo R (1986a) The problem of “staging” in childhood acute lymphoblastic leukemia: a review. Med Pediatr Oncol 14: 121–123
Mastrangelo R (1986b) Report and recommendations of the Rome workshop concerning poor-prognosis ALL in children: Biologic bases for staging, stratification, and treatment. Med Pediatr Oncol 14: 191–194
Reiter A, Schrappe M, Ludwig WD, Hiddemann W, Sauter S, Henze G, Zimmermann M, Lampert F, Havers W, Niethammer D, Odenwald E, Ritter J, Mann G, Welte K, Gadner H and Riehm H (1994) Chemotherapy of 998 unselected childhood acute lymphoblastic leukemia patients. Results and conclusions of the multicenter trail ALL-BFM 86. Blood 84: 3122–3133
Robison LL, Sather HN, Coccia PF, Nesbit ME and Hammond GD (1980) Assessment of the interrelationship of prognostic factors in childhood acute lymphoblastic leukemia. Am J Pediatr Hematol Oncol 2: 5–13
Royston D and Altman DG (1994) Regression using fractional polynomials of continuous covariates: parsimonious parametric modelling. Applied Statistics 43: 429–467
Sauerbrei (1999) Building multivariable prognostic and diagnostic models: transformation of the predictors by using fractional polynomials. J R Statist Soc A 162: 71–94
Schaison G, Olive D, Leverger G, Vannier JP, De Lumley L, Bancillon A and Cornu G (1990) Treatment of acute lymphoblastic leukemia: protocol Fralle 83–85. Haematol Blood Transfu 33: 467–472
Schemper M and Smith TL (1996) A note on quantifying follow-up in studies of failure time. Controlled Clin Trials 17: 343–346
Schorin MA, Blattner S, Gelber RD, Tarbell NJ, Donnelly M, Dalton V, Cohen HJ and Sallan SE (1994) Treatment of childhood acute lymphoblastic leukemia: results of Dana-Farber Cancer Institute/Children's hospital acute lymphoblastic leukemia consortium protocol 85–01. J Clin Oncol 12: 740–747
Schrappe M, Beck J, Brandeis WE, Feickert HJ, Gadner H, Graf N, Havers W, Henze G, Jobke A and Kornhuber B (1987) Treatment of acute lymphoblastic leukemia in childhood and adolescence: results of the multicenter therapy study ALL-BFM 81. Klin Pädiatr 199: 133–150
Smith M, Arthur D, Camitta B, Caroll AJ, Crist W, Gaynon P, Gelber R, Heerema N, Korn EL, Link M, Murphy S, Pui CH, Pullen J, Reaman G, Sallan SE, Sather H, Shuster J, Simon R, Trigg M, Tubergen D, Uckun F and Ungerleider R (1996) Uniform approach to risk-classification and treatment assignment for children with ALL. J Clin Oncol 14: 18–24
Tivey H (1952) Prognosis for survival in the leukemias of childhood. Pediatrics 10: 48–59
Zuelzer WW (1964) Implications of long-term survival in acute stem cell leukemia of childhood treated with composite cyclic therapy. Blood 24: 477–494
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Donadieu, J., Auclerc, MF., Baruchel, A. et al. Prognostic study of continuous variables (white blood cell count, peripheral blast cell count, haemoglobin level, platelet count and age) in childhood acute lymphoblastic leukaemia. Analysis of a population of 1545 children treated by the French Acute Lymphoblastic Leukaemia Group (FRALLE). Br J Cancer 83, 1617–1622 (2000). https://doi.org/10.1054/bjoc.2000.1504
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DOI: https://doi.org/10.1054/bjoc.2000.1504