Chemotherapy-induced anaemia during adjuvant treatment for breast cancer: development of a prediction model.
BACKGROUND
At present, oncologists prescribe chemotherapy according to standard dose schedules, and as a result many patients develop serious, dose-limiting toxic effects such as anaemia. We aimed to develop a prediction model for anaemia in patients with breast cancer who were receiving adjuvant chemotherapy.


METHODS
We reviewed medical records of 331 patients who had received adjuvant chemotherapy for breast cancer. Patients were divided randomly into a derivation sample (n=221) and internal-validation sample (n=110). An external sample of 119 patients enrolled onto the control group of a randomised trial of epoetin alfa was used to validate the model further. Multivariable logistic regression was applied to develop the initial model. We then developed a risk-scoring system, ranging from 0 (low risk) to 50 (high risk), based on the final regression variables. A receiver operating characteristic (ROC) curve analysis was done to measure the accuracy of the scoring system when applied to both validation samples.


RESULTS
The risk of anaemia increased as the pretreatment haemoglobin concentration decreased and was reduced with successive chemotherapy cycles. Risk was also predicted by a platelet count of 200x10(9) cells/L or less before chemotherapy, age 65 years or older, type of adjuvant chemotherapy, and use of prophylactic antibiotics. ROC analysis had acceptable areas under the curve of 0.88 for the internal-validation sample and 0.84 for the external validation sample. A risk score of > or = 24 to < 25 before chemotherapy was identified as the optimum cut-off for maximum sensitivity (83.5%) and specificity (92.3%) of the prediction model.


CONCLUSIONS
The application and continued refinement of this prediction model will help oncologists to identify patients at risk of developing anaemia during chemotherapy for breast cancer, and might enhance patient-centred care by the application of anaemia treatment in a proactive and appropriate way.
Dranitsaris
George
G
Toronto Sunnybrook Regional Cancer Centre, Ontario, Canada. gdranit@ca.inter.net
Clemons
Mark
M
Verma
Sunil
S
Lau
Cathy
C
Vincent
Mark
M
D000368:Aged; D000740:Anemia / Q000139:chemically induced* / Q000188:drug therapy; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000009:adverse effects*; D001943:Breast Neoplasms / Q000188:drug therapy*; D017024:Chemotherapy, Adjuvant / Q000009:adverse effects; D000068817:Epoetin Alfa; D004921:Erythropoietin / Q000627:therapeutic use; D005260:Female; D000069585:Filgrastim; D016179:Granulocyte Colony-Stimulating Factor / Q000627:therapeutic use; D006397:Hematinics / Q000627:therapeutic use; D006801:Humans; D016015:Logistic Models; D008499:Medical Records; D008875:Middle Aged; D011237:Predictive Value of Tests; D012372:ROC Curve; D011994:Recombinant Proteins; D012307:Risk Factors
D006397:Hematinics; D011994:Recombinant Proteins; D004921:Erythropoietin; D016179:Granulocyte Colony-Stimulating Factor; D000068817:Epoetin Alfa; D000069585:Filgrastim