Predictors of response to erythropoiesis-stimulating agents (ESA) in cancer patients: the role of baseline serum epoetin level

Early erythroferrone levels can predict the long-term haemoglobin responses to erythropoiesis-stimulating agents

BACKGROUND AND PURPOSE

Our previous study reported that erythroferrone (ERFE), a newly identified hormone produced by erythroblasts, responded to recombinant human erythropoietin (rHuEPO) sensitively but its dynamics was complicated by double peaks and circadian rhythm. This study intends to elucidate the underlying mechanisms for the double peaks of ERFE dynamics and further determine whether early ERFE measurements can predict haemoglobin responses to rHuEPO.

EXPERIMENTAL APPROACH

By using the purified recombinant rat ERFE protein and investigating its deposition in rats, the production of ERFE was deconvoluted. To explore the role of iron in ERFE production, we monitored short-term changes of iron status after injection of rHuEPO or deferiprone. Pharmacokinetic/pharmacodynamic (PK/PD) modelling was used to confirm the mechanisms and examine the predictive ability of ERFE for long-term haemoglobin responses.

KEY RESULTS

The rRatERFE protein was successfully purified. The production of ERFE was deconvoluted and showed two independent peaks (2 and 8 h). Transient iron decrease was observed at 4 h after rHuEPO injection and deferiprone induced significant increases of ERFE. Based on this mechanism, the PK/PD model could characterize the complex dynamics of ERFE. In addition, the model predictions further revealed a stronger correlation between ERFE and haemoglobin peak values than that for observed values.

CONCLUSIONS AND IMPLICATIONS

The complex dynamics of ERFE should be composited by an immediate release and transient iron deficiency-mediated secondary production of ERFE. The early peak values of ERFE, which occur within a few hours, can predict haemoglobin responses several weeks after ESA treatment.

Pathogenesis and Treatment Options of Cancer Related Anemia: Perspective for a Targeted Mechanism-Based Approach

Cancer-related anemia (CRA) is a common sign occurring in more than 30% of cancer patients at diagnosis before the initiation of antineoplastic therapy. CRA has a relevant influence on survival, disease progression, treatment efficacy, and the patients' quality of life. It is more often detected in patients with advanced stage disease, where it represents a specific symptom of the neoplastic disease, as a consequence of chronic inflammation. In fact, CRA is characterized by biological and hematologic features that resemble those described in anemia associated to chronic inflammatory disease. Proinflammatory cytokine, mainly IL-6, which are released by both tumor and immune cells, play a pivotal action in CRA etiopathogenesis: they promote alterations in erythroid progenitor proliferation, erythropoietin (EPO) production, survival of circulating erythrocytes, iron balance, redox status, and energy metabolism, all of which can lead to anemia. The discovery of hepcidin allowed a greater knowledge of the relationships between immune cells, iron metabolism, and anemia in chronic inflammatory diseases. Additionally, chronic inflammation influences a compromised nutritional status, which in turn might induce or contribute to CRA. In the present review we examine the multifactorial pathogenesis of CRA discussing the main and novel mechanisms by which immune, nutritional, and metabolic components affect its onset and severity. Moreover, we analyze the status of the art and the perspective for the treatment of CRA. Notably, despite the high incidence and clinical relevance of CRA, controlled clinical studies testing the most appropriate treatment for CRA are scarce, and its management in clinical practice remains challenging. The present review may be useful to indicate the development of an effective approach based on a detailed assessment of all factors potentially involved in the pathogenesis of CRA. This mechanism-based approach is essential for clinicians to plan a safe, targeted, and successful therapy, thereby promoting a relevant amelioration of patients' quality of life.

Occurrence and determinants of poor response to short-term pre-operative erythropoietin treatment

BACKGROUND

This study aimed to explore the occurrence and determinants of poor response to short-term pre-operative erythropoietin treatment and the effect of such poor response on transfusion in total hip arthroplasty patients.

METHODS

We studied total hip arthroplasty patients who received erythropoietin before surgery. The primary outcome was the pre-operative increase in haemoglobin (delta haemoglobin) as response to erythropoietin therapy. Additionally, patients were classified in tertiles based on this delta haemoglobin: poor responders (cases), responders and good responders (controls) to erythropoietin. Patient characteristics, comedication and co-morbidity were collected as potential determinants of erythropoietin response. Regression techniques were used to estimate the strength of the associations and to assess the effect of poor response on transfusion requirement.

RESULTS

A total of 379 patients receiving erythropoietin were eligible to enter the study. Mean delta haemoglobin was 19.3 g/l (standard deviation 9.4). Factors significantly associated with delta haemoglobin were the use of angiotensin II antagonists [-3.1 g/l; 95% confidence interval (CI) -5.7 to -0.6] and vitamin K antagonists (-6.9 g/l; 95% CI -10.0 to -0.2), together with body mass index (BMI) (-0.3 g/l per unit>; 95% CI -0.5 to -0.2). The additional case-control analysis yielded comparable results. Poor response to erythropoietin was associated with an increased transfusion risk (odds ratio 4.6, 95% CI 2.0-11).

CONCLUSION

Use of angiotensin II receptor antagonists and vitamin K antagonists, and having a high BMI were determinants of poor response to short-term pre-operative erythropoietin treatment in total hip arthroplasty patients. Poor responders had a higher risk for perioperative blood transfusion.

Population pharmacokinetic-pharmacodynamic modeling of biological agents: when modeling meets reality

The pharmacokinetics (PK) and pharmacodynamics (PD) of many biological agents (biologics) have inherent complexities requiring specialized approaches to develop reliable, unbiased models. Three cases are covered: preponderance of zero values, nonresponder subpopulations, and adaptive dosing. Engineered biologics exhibit high affinity for target receptors. Biologics can saturate receptors, abolishing free receptor levels for protracted periods. Consequently, the distribution of observations can be heavy at, and near, the boundary. A 2-part model (ie, a truncated δ log-normal distribution) may be appropriate. Mixture models identify subpopulations based on bimodal or multimodal distributions of η values. With biologics, PD may be compromised because of lack of receptors, or the PD may be affected because of other events resulting in erratic excursions. Nonresponders exhibit a random walk-around placebo trajectory, resulting in high residual variability. The distributions of etas are often badly skewed or polymodal. An indescribable mixture model separates subjects who are nonresponders, providing diagnostic pharmacologic information on the drug. Many biologics use PD-based adaptive dosing. During model development, data used for model development include adaptive dosing. For simulation, adaptive dosing must be implemented. Failure to account for dose adjustments results in biased or inflated prediction intervals because subjects in the simulated data undergo inappropriate dose adjustments.