Validation of ACG Case-mix for equitable resource allocation in Swedish primary health care

<p>Abstract</p> <p>Background</p> <p>Adequate resource allocation is an important factor to ensure equity in health care. Previous reimbursement models have been based on age, gender and socioeconomic factors. An explanatory model based on individual need of primary health care (PHC) has not yet been used in Sweden to allocate resources. The aim of this study was to examine to what extent the ACG case-mix system could explain concurrent costs in Swedish PHC.</p> <p>Methods</p> <p>Diagnoses were obtained from electronic PHC records of inhabitants in Blekinge County (approx. 150,000) listed with public PHC (approx. 120,000) for three consecutive years, 2004-2006. The inhabitants were then classified into six different resource utilization bands (RUB) using the ACG case-mix system. The mean costs for primary health care were calculated for each RUB and year. Using linear regression models and log-cost as dependent variable the adjusted R²was calculated in the unadjusted model (gender) and in consecutive models where age, listing with specific PHC and RUB were added. In an additional model the ACG groups were added.</p> <p>Results</p> <p>Gender, age and listing with specific PHC explained 14.48-14.88% of the variance in individual costs for PHC. By also adding information on level of co-morbidity, as measured by the ACG case-mix system, to specific PHC the adjusted R²increased to 60.89-63.41%.</p> <p>Conclusion</p> <p>The ACG case-mix system explains patient costs in primary care to a high degree. Age and gender are important explanatory factors, but most of the variance in concurrent patient costs was explained by the ACG case-mix system.</p

Prognostic impact of early-versus-late responses to different induction regimens in patients with myeloma undergoing autologous hematopoietic cell transplantation: Results from the CALM study by the CMWP of the EBMT

Background In autologous stem cell transplant (ASCT)-eligible myeloma patients, prolonged induction does not necessarily improve the depth of response.Method We analyzed 1222 ASCT patients who were classified based on (a) the interval between induction and stem cell collection, (b) the type of induction regimen: BID (Bortezomib, IMiDs, and Dexamethasone), Bortezomib-based, or CTD (Cyclophosphamide, Thalidomide, and Dexamethasone), and (c) the time to best response (Early ie, best response within 4 or 5 months, depending on the regimen vs Late; Good ie, VGPR or better vs Poor).Results The length of induction treatment required to achieve a Good response did not affect PFS (P = .65) or OS (P = .61) post-ASCT. The three types of regimen resulted in similar outcomes: median PFS 31, 27.7 and 30.8 months (P = .31), and median OS 81.7, 92.7, and 77.4 months, respectively (P = .83). On multivariate analysis, neither the type nor the duration of the induction regimen affected OS and PFS, except for Early Good Responders who had a better PFS compared to Early Poor Responders (HR = 1.21, P-value = .02). However, achieving a Good response at induction was associated with a better response (&gt;= VGPR) post-transplant.Conclusion The kinetics of response did not affect outcomes

Pharmacokinetic and -dynamic modelling of G-CSF derivatives in humans

<p>Abstract</p> <p>Background</p> <p>The human granulocyte colony-stimulating factor (G-CSF) is routinely applied to support recovery of granulopoiesis during the course of cytotoxic chemotherapies. However, optimal use of the drug is largely unknown. We showed in the past that a biomathematical compartment model of human granulopoiesis can be used to make clinically relevant predictions regarding new, yet untested chemotherapy regimen. In the present paper, we aim to extend this model by a detailed pharmacokinetic and -dynamic modelling of two commonly used G-CSF derivatives Filgrastim and Pegfilgrastim.</p> <p>Results</p> <p>Model equations are based on our physiological understanding of the drugs which are delayed absorption of G-CSF when applied to the subcutaneous tissue, dose-dependent bioavailability, unspecific first order elimination, specific elimination in dependence on granulocyte counts and reversible protein binding. Pharmacokinetic differences between Filgrastim and Pegfilgrastim were modelled as different parameter sets. Our former cell-kinetic model of granulopoiesis was essentially preserved, except for a few additional assumptions and simplifications. We assumed a delayed action of G-CSF on the bone marrow, a delayed action of chemotherapy and differences between Filgrastim and Pegfilgrastim with respect to stimulation potency of the bone marrow. Additionally, we incorporated a model of combined action of Pegfilgrastim and Filgrastim or endogenous G-CSF which interact via concurrent receptor binding. Unknown pharmacokinetic or cell-kinetic parameters were determined by fitting the predictions of the model to available datasets of G-CSF applications, chemotherapy applications or combinations of it. Data were either extracted from the literature or were received from cooperating clinical study groups. Model predictions fitted well to both, datasets used for parameter estimation and validation scenarios as well. A unique set of parameters was identified which is valid for all scenarios considered. Differences in pharmacokinetic parameter estimates between Filgrastim and Pegfilgrastim were biologically plausible throughout.</p> <p>Conclusion</p> <p>We conclude that we established a comprehensive biomathematical model to explain the dynamics of granulopoiesis under chemotherapy and applications of two different G-CSF derivatives. We aim to apply the model to a large variety of chemotherapy regimen in the future in order to optimize corresponding G-CSF schedules or to individualize G-CSF treatment according to the granulotoxic risk of a patient.</p