Clonal expansion of T/NK-cells during tyrosine kinase inhibitor dasatinib therapy.

Dasatinib, a broad-spectrum tyrosine kinase inhibitor (TKI), predominantly targets BCR-ABL and SRC oncoproteins and also inhibits off-target kinases, which may result in unexpected drug responses. We identified 22 patients with marked lymphoproliferation in blood while on dasatinib therapy. Clonality and immunophenotype were analyzed and related clinical information was collected. An abrupt lymphocytosis (peak count range 4-20 x 10(9)/l) with large granular lymphocyte (LGL) morphology was observed after a median of 3 months from the start of therapy and it persisted throughout the therapy. Fifteen patients had a cytotoxic T-cell and seven patients had an NK-cell phenotype. All T-cell expansions were clonal. Adverse effects, such as colitis and pleuritis, were common (18 of 22 patients) and were preceded by LGL lymphocytosis. Accumulation of identical cytotoxic T cells was also detected in pleural effusion and colon biopsy samples. Responses to dasatinib were good and included complete, unexpectedly long-lasting remissions in patients with advanced leukemia. In a phase II clinical study on 46 Philadelphia chromosome-positive acute lymphoblastic leukemia, patients with lymphocytosis had superior survival compared with patients without lymphocytosis. By inhibiting immunoregulatory kinases, dasatinib may induce a reversible state of aberrant immune reactivity associated with good clinical responses and a distinct adverse effect profile.

Sepsis, low platelet nadir at mobilization and previous IFN use predict stem cell mobilization failure in patients with multiple myeloma.

BACKGROUND: Successful stem cell mobilization is a prerequisite for autologous blood cell transplantation. We analyzed factors that may predict the success of stem cell mobilization in patients with multiple myeloma (MM). METHODS: We analyzed 124 consecutive patients and compared those who failed to mobilize a sufficient amount of CD34(+) cells (peak blood CD34(+) cell count <20x10(6)/L) (n=20) with those with successful mobilization (n=104). The peak blood CD34(+) cell count after mobilization was used as the marker of mobilization success against which the various predictive factors were tested. RESULTS: In univariate analysis the best predictive factors for mobilization failure were the number of different chemotherapy regimens (P<0.001), number of chemotherapy cycles (P<0.001), time from diagnosis to mobilization (P<0.001) and previous use of IFN (P<0.001). The distributions of treatment responses at mobilization were similar in the groups with successful and unsuccessful mobilization, and were CR or VGPR in 10% of all patients, PR in 54% and stable or progressive disease in 36%. Regarding the mobilization-related factors, lower leukocyte nadir (P<0.001), longer duration of leukocyte counts <1x10(9)/L (P<0.001), lower platelet nadir (P=0.001), longer duration of platelet counts <20x10(9)/L (P<0.001) and the occurrence of sepsis after the mobilization therapy (P=0.001) were significantly associated with mobilization failure. In multivariate analysis, the amount of earlier chemotherapy cycles (P=0.002), low platelet nadir (P=0.020), occurrence of sepsis at mobilization (P=0.040) and previous use of IFN (P=0.052) remained as significant predictive factors for mobilization failure. DISCUSSION: Predicting the success of stem cell mobilization beforehand may have important practical consequences. By identifying those patients who will fail to mobilize stem cells, unnecessary mobilization and collection attempts can be avoided.

Validation of a new method for patient classification, the Oulu Patient Classification.

At Vasa Central Hospital in Western Finland a further development of the Oulu Patient Classification (OPC) has been made by the development of weight coefficients and by estimating the nursing care intensity per nurse. The daily level of nursing care intensity of a ward is expressed by the number of nursing care intensity points per nurse. This article presents results from a validity test of the OPC at Vasa Central Hospital. The test was carried out by comparing the daily patient classifications by means of the OPC against measurements made by means of a new measuring instrument, the 'Professional Assessment of Optimal Nursing Care Intensity Level' (PAONCIL) developed at the Vasa Central Hospital. The study was implemented in eight wards during a period of 3 months. The data material consisted of two parts, the daily patient classifications based on the OPC (n = 19 324) and the measurements by means of the PAONCIL forms (n = 8458). Simple and multiple linear regression analyses were used as statistical methods in quantifying the linear relationship between the two interval-scaled variables. In the test of concurrent validity the coefficient of determination was 0.366, i.e. the association between these two indicators is fairly strong (36.6%). The testing of construct validity showed that the construct validity of the indicator hardly deteriorates as a result of the patients being placed in separate nursing care intensity categories. There was a clear correlation between the scores allotted by the indicator to the six different sub-areas of nursing care. When examining the construct validity of the OPC, no factors with independent explanatory power in predicting PAONCIL values were discovered other than those of the OPC. The OPC proved on the basis of this research material and these statistical methods to possess fairly adequate validity, and thus there is a good basis for further research and a development of nursing care.

Professional assessment of optimal nursing care intensity level. A new method for resource allocation as an alternative to classical time studies.

In the article a new method is presented for allocation of staff resources, 'Professional Assessment of Optimal Nursing Care Intensity Level' (PAONCIL). This method is presented as an alternative to classical time study, which has traditionally been considered to belong to systems for patient classification. By means of this method the optimal nursing care intensity level for individual wards can be established. The study comprised 8 wards, and the nurses working in these wards provided a total of 8,458 professional assessments of optimal nursing care intensity levels. The material was analysed by means of simple linear regression analysis. The nursing care intensity scores per nurse in a single ward were used as independent variables and the average PAONCIL score for the same calendar day was used as a dependent variable. The average determination coefficient for different wards were 0.37; the PAONCIL instrument thus explained 37% of the nursing care intensity/nurse variation. This corresponded to a linear correlation of 0.60. In five out of six wards for adults the optimal nursing care intensity/nurse scores were close to each other, ranging from 3.0 to 3.6. The advantage of the PAONCIL method is that it can be easily implemented in a ward, can be used time and again, is advantageous and is based on quality aspects. The PAONCIL method has been developed on the basis of a caring science perspective and can be seen as an administrative method for the nurse manager, with whose help 'good care' can become possible.