Value of incorporating newly identified risk factors into risk prediction for chemotherapy‐induced febrile neutropenia

Abstract

Several comorbidities have recently been shown to affect risk of chemotherapy‐induced febrile neutropenia (FN). Here, we evaluated the added predictive value of these comorbidities beyond established FN risk factors. A retrospective cohort study was conducted among adult patients diagnosed with cancer and treated with chemotherapy at Kaiser Permanente Southern California between 2000 and 2009. The study cohort was equally split into training and validation datasets to develop and evaluate the performance of FN risk prediction models in the first chemotherapy cycle. A reference model was developed based on the model proposed by Lyman et al (Cancer 2011;117:1917). A new model was developed by incorporating the newly identified comorbidities such as rheumatoid conditions and thyroid disorders into the reference model. Area under the receiver operating characteristic curve (AUROCC), risk reclassification, and integrated discrimination improvement (IDI) were used to evaluate the potential improvement of FN risk prediction by incorporating comorbidities. A total of 15 279 patients were included; 4.2% experienced FN in the first chemotherapy cycle. Including comorbidities in FN risk prediction did not improve AUROCC (reference model 0.71 vs new model 0.72). A significant improvement in individual‐level FN risk prediction was indicated by IDI (P = .02). However, significant improvement in risk reclassification was not observed overall (although 6% of all patients were more accurately classified for their FN risk level, 5% were less accurately classified) or when examining predicted FN risk among patients who did and did not develop FN. Incorporating several new comorbidities into FN prediction led to improved FN risk prediction in the first chemotherapy cycle, although the observed improvements were small and might not be clinically relevant.

The Impact of Baseline Risk Factors on the Incidence of Febrile Neutropenia in Breast Cancer Patients Receiving Chemotherapy with Pegfilgrastim Prophylaxis: A Real-World Data Analysis

“…Importantly, the previously discussed studies and the majority of published literature regarding patient-specific FN risk factors were developed by studying patients who were not receiving primary prophylaxis. [30][31]37 This study is the first, to our knowledge, to demonstrate the substantial impact of patient-specific risk factors on FN incidence in a population of patients all receiving pegfilgrastim primary prophylaxis in the United States. Because of this, it further validates the importance and absolute necessity of using statistical techniques (eg, propensity score matching) to control for these variables in any real-world study that purports to demonstrate a difference in FN incidence between two pegfilgrastim products.…”

Improved risk prediction of chemotherapy‐induced neutropenia—model development and validation with real‐world data

“…The risk-reducing effect of reduced RDI was consistent with previous reports. 14,15 Finally, among all the pre-treatment laboratory test results, only lower ANC and thrombocyte counts were associated with elevated NI risk in the final model. Similar effects of ANC and thrombocyte counts on the risk of neutropenic complications have been reported also before.…”

<p>A comparative experimental study of analgesic activity of a novel non-steroidal anti-inflammatory molecule – zaltoprofen, and a standard drug – piroxicam, using murine models</p>

“…In another observational, prospective study, zaltoprofen in combination with topical anesthetic gel was found to be superior to anesthetic gel alone in controlling cystoscopy-related pain 23. Recently, a study published in Cancer Medicine concluded that zaltoprofen could be a promising drug against the malignant phenotypes in chondrosarcomas via activation of PPAR γ and inhibition of MMP2 activity 24Figure 3Tail flick latency with different drug dosages in tail flick model of pain in mice. Notes: *** represents p -values < 0.001; a denotes NS control at different time intervals, b denotes test and standard drugs compared to NS.…”