REPLY POSTS:Reply separately to two of your classmates article critique’s posts (See attached classmates posts, post#1 and post#2). – Use at least two scholarly references per peer post. The expectati

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: My background for you to have as a reference: I am currently enrolled in the Advance Nurse Practitioner Program, I am a Registered Nurse, I work at a Psychiatric Hospital.

REPLY POSTS:Reply separately to two of your classmates article critique’s posts (See attached classmates posts, post#1 and post#2). – Use at least two scholarly references per peer post. The expectati
RUNNING HEAD: SICKLE CELL ANEMIA Discussion Post – Week 4 Sickle Cell Anemia Jennifer Pike The purpose of this discussion post is to critique a research article focused on the treatment of Sickle Cell Anemia (SCA) with Hydroxyurea. SCA is attributed to an inherited characteristic that leads to the formation of abnormal hemoglobin, referred to as hemoglobin S (HbS) (Hubert & VanMeter, 2018). There are over 300,000 infants born each year worldwide with sickle cell anemia, it is an autosomal recessive disease. The clinical manifestations of SCA can include hemolytic anemia, vaso-occlusive crisis, and bacterial susceptibility that can have a lasting impact on many of the organs (Becker et al., 2019). Many of the signs and symptoms of SCA do not appear until a child is around 12 months of age when their fetal hemoglobin has been replaced by the HbS, the amount of hemoglobin that is replaced by HbS determines how severe the illness will be (Hubert & VanMeter 2018). One of the medications used for the treatment of SCA is Hydroxyurea which when effective for an individual is able to reduce the frequency of vaso-occlusive episodes and prolong the lifespan. The article titled, “Optimizing Hydroxyurea Treatment for Sickle Cell Disease Patients: The Pharmacokinetic Approach,” the article was published in the Journal of Clinical Medicine in October 2019. The authors include Charlotte Nazon, Amelia-Naomi Sabo, Guillaume Becker, Jean-Marc Lessinger, Veronique Kemmel, and Catherine Paillard. The purpose of the article presented is to optimize and encourage the use of Hydroxyurea in SCA patients by showing the efficacy in reducing the frequency of vaso-occlusive episodes, hospitalizations, need for blood transfusions, and overall improved quality of life. The authors used a method of dose increasing in order to reach optimal level of treatment. The participants of the study were patients with SCA that were under 20 years of age and being treated with Hydroxyurea currently by the authors hospital of affiliation between February and May 2018. The sample size consisted of 9 patients that were on Hydroxyurea for multiple vaso-occlusive events or acute chest syndrome. According to the researchers most of the participants in the study had already been on Hydroxyurea for more than four years with a daily dose of 12.9 to 24.6 mg/kg/day. Plasma samples of the participant was collected at pre-determined times including, pre-dose, at 10 minutes, 20 minutes, 1 hour, 2 hour, 4 hour, and the 6 hour mark after dosing of the patients usual dose. The levels of neutrophil count, reticulocyte count and platelet count were monitored in order to ensure maximum dose tolerance could be reached without the risk of toxicity. None of the patients in the study were able to reach maximum dose tolerance with myelosuppression. The inability of the participants to reach maximum dose tolerance was attributed to two factors. The dose used on the patients in this study was smaller than the doses used in previous studies with better results. Another factor that was brought up was patients’ compliance to taking the medication. Four out of the 9 patients were suspected as being non-compliant due their low MCV levels. The authors described another gap and limitation of this research study is using the patients as reporting compliance as this can often be unreliable method of knowing whether or not they were truly compliant. Another large limitation of this study is the sample size of only 9 patients, this doesn’t allow for the most accurate or widely accepted number of evidence having such a small sample size. What is made apparent in this research study is the importance of proper hydroxyurea dosing to improve the lives of patients with SCA. This is important for any APRN who is treating a patient with SCA at the level of preventive care to optimize and pro-long their lives. The use of Hydroxyurea is widely known to help reduce vaso-occlusive episodes is not as widely used as it could or should be. SCA being prominent starting in early childhood can bring some fears in use of such a strong medication. Parents are often fearful of the medication and the side effects that can happen without having significant knowledge of the benefits of the medication (Bogen et al., 2015). As APRNs taking care of children or anyone with SCD it is important to be up to date of the proper dosing and usage of Hydroxyurea because it is one of the only medications that is approved to help. Bogen et al., 2015, says that providers should offer hydroxyurea to all pediatric patients with severe SCD to encourage that the parents have shared decision making when it comes to the treatment of their child. This article is important to highlight the usage of the medication and I would recommend this to any provider or colleague who was treating children with SCD who needed guidance or any education on the dosage and use of the medication. References: Becker, G., Kemmel, V., Lessinger, J.-M., Paillard, C., Nazon, C., & Sabo, A.-N. (2019). Optimizing Hydroxyurea Treatment for Sickle Cell Disease Patients: The Pharmacokinetic Approach. Journal of Clinical Medicine, 8(10), 1701–1701. https://doi.org/10.3390/jcm8101701 Bogen, D. L., Creary, S., Krishnamurti, L., Ross, D., & Zickmund, S. (2015). Hydroxyurea therapy for children with sickle cell disease: Describing how caregivers make this decision. BMC Research Notes, 1. https://doi.org/10.1186/s13104-015-1344-0 Hubert, R., & VanMeter, K. (2018). Gould’s Pathophysiology for the Health Professions (Sixth). Elsevier.
REPLY POSTS:Reply separately to two of your classmates article critique’s posts (See attached classmates posts, post#1 and post#2). – Use at least two scholarly references per peer post. The expectati
0 Running head: ARTICLE CRITIQUE Chapter 11: Lymphedema The purpose of this paper is to discuss lymphedema and critique an article on the topic. Lymphedema is when there is an obstruction in the lymphatic vessels that cause the tissues in the extremities to swell (Hubert & Vanmeter, 2018). This also allows for accumulation of lymph in the tissues as well. Commonly, this disorder is congenital and may involve the lymph nodes along with the vessels (Hubert & Vanmeter, 2018). It can also be caused by blockage of the lymph vessels due to parasitic worms (Hubert & Vanmeter, 2018). When the lymph states to build up in the body, the more the extremity swells (Huber & Vanmeter, 2018). As lymphedema continues to progress over time, the extremity becomes enlarged, firm and painful (Hubert & Vanmeter, 2018). Lymphedema can be chronic as well, which leads to frequent infection (Hubert & Vanmeter, 2018). According to Johns Hopkins Medicine (2020), lymphedema can occur after cancer surgery when lymph nodes are removed. Authors Rebecca J. Tsai, Leslie K. Dennis, Charles F. Lynch, Linda G. Snetselaar, Gideon K. D. Zamba, Carol Scott-Conner published an article on lymphedema after breast cancer entitled “Lymphedema following breast cancer: The importance of surgical methods and obesity” Published to Front Women’s Health in 2018. The purpose of the article is to discuss the research that the authors have conducted on the association between developing lymphedema after cancer surgery and personal risk factors (Tsai et al., 2018). This research will allow for them to better understand if there are certain factors that make a person more at risk for developing lymphedema after cancer surgery. The literature was drawn from a systemic approach. This is because it focuses on a specific question and critically appraises all relevant research. The review focuses on cause and effect meaning how does one issue effect the other. In this case, the authors are correlating developing lymphedema after surgery and certain risk factors that can affect this. Tsai et al. (2018) identify concern that the measures of the study are from subject self-reporting. The authors feel that there can be issues with self-reporting because the patients do not always participate until the end of the study. The aim of the study is to understand if there is a correlation between arm lymphedema and certain personal risk factors (Tasi et al., 2018). To achieve an accurate study, the authors used a population-based cohort design. This allows for better understanding of the research for this specific population of women. The sample was obtained in Iowa from 2004 to 2010. Tsai et al. (2018) states that the women who met the criteria, completed a short telephone interview about their lymphedema status, arm activities, demographics and chronic conditions that they currently have. The patients were confirmed to have lymphedema from physician reports and the presence of at least four major arm symptoms that can occur with the disease (Tsai et al., 2018). There were 522 participants in the study, which seems to be an adequate size for a population-based cohort design. The study showed that lymphedema was identified in 102 of the 522 patients (Tsai et al., 2018). The results showed that people who had radiation and some dissection if the axilla were more at risk for lymphedema after breast cancer surgery (Tsai et al., 2018). Tsai et al. (2018) states that the women who were the most likely to have lymphedema had a body mass index above 40. This shows that obesity, the characteristics of the cancer and the methods used in surgery were all major factors in the patient developing lymphedema (Tsai et al., 2018). The authors found that obesity promotes the inflammation of the body which leads to issues with lymphedema. The authors also found that women who were younger had a higher chance of developing lymphedema as well. The authors are satisfied with the results and do not mention a need for further testing (Tsai et al., 2018). The article is greatly recommended as a nurse and a future advanced practice nurse. This article is easy to comprehend and has pertinent information that can be used in practice. The information can be useful when assessing patients who have had breast cancer surgery. Knowing and understanding the risk factors for developing lymphedema after breast cancer surgery can allow for preventative care for the patients who are most at risk. It may not be completely curable, but there are certain steps that can be taken to reduce the symptoms or even keep it from starting in the first placed (Johns Hopkins Medicine, 2020). It is apparent that advanced practice nurses should understand the signs and symptoms of developing lymphedema so that it can be treated adequately. References Hubert, R. & VanMeter, K. C. (2018). Gould’s pathophysiology for the health professions. St. Louis, MO: Elsevier Saunders. Johns Hopkins Medicine. (2020). Breast cancer: lymphedema after treatment. Retrieved from https://www.hopkinsmedicine.org/health/conditions-and-diseases/breast-cancer/breast-cancer-lymphedema-after-treatment Tsai R. J., Dennis, L. K., Lynch, C. F., Snetselaar, L. G., Zamba, G. K. D., Scott-Conner, C. (2018). Lymphedema following breast cancer: the importance of surgical methods and obesity. Front Women’s Health, 3(2), 1-17. References Lastname, C. (2008). Title of the source without caps except Proper Nouns or: First word after colon. The Journal or Publication Italicized and Capped, Vol#(Issue#), Page numbers. Lastname, O. (2010). Online journal using DOI or digital object identifier. Main Online Journal Name, Vol#(Issue#), 159-192. doi: 10.1000/182 Lastname, W. (2009). If there is no DOI use the URL of the main website referenced. Article Without DOI Reference, Vol#(Issue#), 166-212. Retrieved from http://www.mainwebsite.org
REPLY POSTS:Reply separately to two of your classmates article critique’s posts (See attached classmates posts, post#1 and post#2). – Use at least two scholarly references per peer post. The expectati
Article Optimizing Hydroxyurea Treatment for Sickle Cell Disease Patients: The Pharmacokinetic Approach Charlotte Nazon 1 , Amelia-Naomi Sabo 2 , 3 , Guillaume Becker 3 , 4 , Jean-Marc Lessinger 2 , V ²ronique Kemmel 2 , 3 , * and Catherine Paillard 1 , 5 , * 1 Hæpitaux Universitaires de Strasbourg, Centre de comp ²tence pour les maladies constitutionnelles du globule rouge et de l’ ²rythropoï ±se, Service d’h ²matologie oncologie p ²diatrique, Avenue Moli ±re, 67200 Strasbourg, France; [email protected] 2Laboratoire de Pharmacologie et Toxicologie Neurocardiovasculaire, Facult ²de M ²decine, 11 rue Humann, 67085 Strasbourg, France; [email protected] (A.-N.S.); [email protected] (J.-M.L.) 3 Hæpitaux Universitaires de Strasbourg, H æpital de Hautepierre, Laboratoire de Biochimie et Biologie Mol ²culaire, Avenue Moli ±re, 67200 Strasbourg, France; [email protected] 4 Hæpitaux Universitaires de Strasbourg, Service de la Pharmacie, Avenue Moli ±re, 67200 Strasbourg, France 5 Laboratoire d’ImmunoRhumatologie Mol ²culaire, INSERM UMR_S 1109, LabEx Transplantex, F ²d ²ration de M ²decine Translationnelle de Strasbourg, 4 rue Kirschleger, 67085 Strasbourg Cedex, France * Correspondence: [email protected] (V.K.); [email protected] (C.P.); Tel.: +33-(0)-3-88-12-75-33 (V.K.); +33-(0)-3-88-12-88-23 (C.P.) Received: 21 August 2019; Accepted: 11 October 2019; Published: 16 October 2019 Abstract: Background: Hydroxyurea (HU) is a FDA- and EMA-approved drug that earned an important place in the treatment of patients with severe sickle cell anemia (SCA) by showing its e cacy in many studies. This medication is still underused due to fears of physicians and families and must be optimized. Methods: We analyzed our population and identi ed HU pharmacokinetic (PK) parameters in order to adapt treatment in the future. Working with a pediatric population, we searched for the most indicative sampling time to reduce the number of samples needed. Results: Nine children treated by HU for severe SCA were included for this PK study. HU quanti cation was made using a validated gas chromatography /mass spectrometry (GC /MS) method. Biological parameters (of e ectiveness and compliance) and clinical data were collected. None of the nine children reached the therapeutic target de ned by Dong et al. as an area under the curve (AUC) =115 h.mg /L; four patients were suspected to be non-compliant. Only two patients had an HbF over 20%. The 2 h sample was predictive of the medication exposure ( r2=0.887). Conclusions: It is urgent to be more e cient in the treatment of SCA, and pharmacokinetics can be an important asset in SCA patients. Keywords: sickle cell disease; sickle cell anemia; hydroxyurea; pharmacokinetics 1. Introduction Sickle cell anemia (SCA) is one of the most common inherited diseases in the world. It a ects more than 300,000 infants born annually worldwide, and the epidemiologic projections show a growing tendency for the years to come (30% increase by 2050) [ 1]. It is an autosomal recessive disease a ecting the red blood cells due to a point missense mutation on the hemoglobin beta chain. This mutation leads to a polymerization of the hemoglobin (Hb), which causes an increased density, dehydration, and deformation of red blood cells, forming the sickle cells [2]. Clinical manifestations of SCA include hemolytic anemia, vaso-occlusive crisis (VOC), and bacterial susceptibility and can have an impact on many organs [3–9]. J. Clin. Med. 2019,8, 1701; doi:10.3390 /jcm8101701www.mdpi.com /journal /jcmJournal of Clinical Medicine J. Clin. Med. 2019,8, 1701 2 of 10Hydroxyurea (HU) is a FDA- and EMA-approved drug that earned an important place in the treatment of patients with severe SCA. It has shown its e cacy in multiple studies by reducing the morbi-mortality and frequency of VOC, transfusions, and hospitalizations for those patients [ 10–16]. Furthermore, HU treatment is associated with improvement in hemoglobin concentration illustrated by increasing mean corpuscular volume (MCV) and Hemoglobin F (HbF) levels [ 17]. One way to adjust HU dose, mostly used in American centers, is to introduce HU at 15–20 mg /kg /day and to make a dose escalation until a mild myelosuppression tolerated by the patient is obtained, which indicates that the maximum tolerated dose (MTD) has been reached [ 18]. The dose escalation of HU depends on three hematological parameters: the neutrophil count (1.5–3 G /L), the reticulocyte count (100–200 G /L), and the platelet count ( >80 G /L) [ 17]. When the MTD is reached, the risk /bene t balance is optimal for the patient [ 19]. Despite the fact that the escalation to MTD has proven to be the best way to dose HU, many European centers use a xed-dose strategy (20 mg/kg /day). The dose escalation method presents some drawbacks: it requires frequent outpatient visits and laboratory tests and usually takes 6 to 12 months; the treatment is usually suboptimal during that time [ 20–22]. The fact that there is a period during which the treatment is not providing any clinical improvement, and that frequent laboratory tests and medical consultations are needed, does not help patient adherence, which is already low in this population [ 23,24]. It has been highlighted by Brandow et al., who showed that the patients who refused HU gave the following reasons: fear of cancer and other side e ects in the majority followed by not wanting to take medication, not wanting to have required laboratory monitoring, or not thinking the medication would work [ 23]. Regarding toxicities, even if we now know that the myelosuppression is transient [ 18,25], that the azoospermia caused by HU could be reversible [ 26], and that there is no evidence it has a genotoxic or a leukemogenic e ect [ 15], the reticence among physicians and families is still strong, leading to an underuse of this treatment [ 23]. Studies showed that the escalation to MTD did not add any toxicities [ 27]. Organ damage begins early in life, worsens over time, and is irreversible. Accordingly, early optimal treatment in young patients who have not yet developed serious or irreversible organ damage is a necessity. Another di culty remains in pharmacokinetic variations of HU. Indeed, for a same dose of HU, drug exposure may vary ve times in adults and three times in children [ 25]. There are major inter-individual variations regarding absorption, pro les, distribution, and clearance of HU [ 28]. Logically, HU is not e cacious at the same dosage for everyone: In a study of Dong et al., posology at MTD ranges from 14.2 to 35.5 mg /kg /day [21]. It makes standard patient care impossible. For these reasons, a personalized dose optimization process that can rapidly identify MTD for individual SCA patients is highly desirable. The main goal of this study was to analyze our population and identify the pharmacokinetic parameters of HU to be able to adapt and optimize their treatment in the future. By doing so, we intend to have a model we can use to adapt the dose of HU and reach the MTD for an earlier clinical bene t for our patients more quickly. Working with a pediatric population, we wanted to nd the most indicative sampling time to reduce the number of blood collections needed. 2. Experimental Section 2.1. Patients We included, prospectively, all the patients with SCA of <20 years of age, treated by HU attending our hospital (H æpitaux Universitaires de Strasbourg, France), for a follow-up consultation between February and May 2018. More than 100 patients with SCA (SS or SC) are followed in our hospital, including 27 treated by HU. In our hospital, HU is introduced at 15 mg /kg /day and normally increased to reach MTD following hematological criteria: the neutrophil count (1.5–3 G /L), the reticulocyte count (100–200 G /L), and the platelet count ( >80 G /L). Although, most of the time, if there is no clinical manifestation of SCA, no dose adjustment is done. J. Clin. Med. 2019,8, 1701 3 of 10All patients and /or parents /guardians provided written informed consent before enrollment in the study. This study received approval from the Institutional review board of Strasbourg University Hospital (DRCI 2018-project n 6112) and the French data protection authority (CNIL-n 2215437). 2.2. Study Design Plasma samples were collected at the following times: pre-dose and at 10 min, 20 min, 1 h, 2 h, 4 h, and 6 h after oral HU administration at the patient’s usual dose. Whole blood samples were transported and /or stored at 2–8 C for a maximum of four h before centrifugation, and then aliquoted plasma was rapidly frozen at 20 C. Demographic information and standard laboratory parameters were collected: Neutrophil, reticulocyte, and platelet counts were measured in turn to identify the individual tolerability of the treatment, hemoglobin, MCV, and the percentage of HbF to monitor the clinical e cacy of HU. We evaluated the adherence of our patients by asking them about the frequency of missed doses over the past six months. Genotypic data were collected, looking for associated alpha thalassemia and haplotype. 2.3. GC-MS The dosage of HU was made by our hospital’s Biochemistry and Molecular Biology Laboratory using a gas chromatography coupled with mass spectrometry (GC-MS) technique (version 2.0, CHU Strasbourg, Strasbourg, France), which can be used routinely. A Thermo Scienti c — ISQ Series (Thermo Fisher Scienti c, Courtaboeuf, France) was used for the analysis. Chromatography was performed on a low polarity RTX-5-MS (30 m 0.25 mm 0.25 m) capillary column, and helium was the carrier gas. The total analysis time of a sample was 13 min. Data were obtained from the Thermo Xcalibur © software ( © 2012 Thermo Fisher Scienti c Inc., version 3.1, Courtaboeuf, France). It is a sensitive and speci c method validated by our local laboratory that is feasible with a low quantity of plasma (50 L). The measurement of this method ranges from 0.79 to 100 mg /L with a detection limit of 0.28 mg /L. 2.4. Modelling and Statistical Analysis The plasma concentration–time data was analyzed by a non-compartmental method to obtain a concentration–time curve. The pharmacokinetics’ parameters were de ned for each patient: the maximum plasma concentration (C max ), the time to reach the C max (Tmax ), and the area under the curve (AUC). The C maxwere identi ed by a graphical analysis. The mean, standard deviation, and median were calculated using Microsoft Excel. The simulated AUC 0–6h were calculated by the linear log trapezoidal rule (version 6, GraphPad Prism, San Diego, CA, USA). 2.5. Optimal Sampling Exploration of the relationship between HU concentration–time and exposition was made. The signi cant linear correlations were de ned by the determination coe cient r2>0.5. AUC was tested by a non-compartmental method. Data analysis was made using the GraphPad Prism ®program (version 6, GraphPad Prism, San Diego, CA, USA). 3. Results 3.1. Characteristics of Patients Nine patients were included, and their characteristics are shown in Table1. These patients were on HU treatment for multiple VOC or acute chest syndrome (ACS). Most of them were treated by HU for more than four years, and their daily doses ranged from 12.9 to 24.6 mg /kg /day. J. Clin. Med. 2019,8, 1701 4 of 10 Table 1. Patient characteristics. Demographic Characteristics Sex ratio M /F 0.8 (4 /5) Age Mean standard deviation 14.4 ( 3.7) Median 16.5 Weight Mean standard deviation 49.9 ( 20.5) Median 49.1 Background (Number of Patients and Percentage) Cholecystectomy 3 (33%) Stroke 1 (11.1%) Abnormal Transcranial doppler episode 1 (11.1%) Osteonecrosis 2 (22.2%)Retinopathy 1 (11.1%) Splenic Sequestration 0 (0%) Pulmonary Hypertension 1 (11.1%) Cardiac Events 1 (11.1%)Kidney Failure 0 (0%) Events per Year: 2016–2018 Period Transfusion /Year Mean Standard Deviation 0.8 Median 0.3 (0–2) Hospitalization /Year Mean standard deviation 1.4 Median (range) 0.6 (0–5.0) VOC /Year Mean Standard Deviation 1.6 Median (range) 1 (0–5.6) ACS Number of Patients >1 ACS 4 (45%) HU Dose (mg /kg /day) Mean Standard Deviation 19.0 ( 4.0) Median (range) 20.4 (12.9–24.6) Time since Introduction of HU (Months) Mean Standard Deviation 63.5 ( 44.6) Median (Range) 58.8 (11.2–138.8) Age at Introduction (Year) Mean Standard Deviation 8.5 ( 4.4) Median (Range) 6.0 (4.0–16.0) HU: Hydroxyurea; VOC: vaso-occlusive crisis; ACS: acute chest syndrome. M: male; F: female. 3.2. Biological Parameters and Self-Reported ComplianceBiological parameters are presented in Table2. Seven patients had an HbF lower than 20%. Four children had a normal or low MCV. None of the patients reached the myelosuppression as de ned earlier as a sign of MTD of HU. None of the patients showed a major hematological toxicity. However, Patient 8 had the lowest neutrophil count, middle MCV, and a low percentage of HbF. We evaluated the adherence of our patients by asking them about the frequency of missed doses over the past six months. We de ned low compliance level as one missed-dose per week or more ( n=2), medium compliance level as one to three missed-doses per month ( n=4), and high compliance level as less than one dose-missed a month (Table2) ( n=3). The genotypic pro le was available only for Patient 8, who is not a carrier of alpha thalassemia and has a Benin /Benin (BEN /BEN) haplotype. J. Clin. Med. 2019,8, 1701 5 of 10 Table 2.Self-reported compliance, biological parameters, and HU intake characteristics of the nine children on HU. Patient Self-Reported Compliance Hb (g /dL) MCV (fL) Retic. (G /L) PNN (G /L) Platelets (G /L) HbF (%) Dose HU (mg /kg /day) Pre-HU Post-HU Pre-HU Post-HU 1 poor 8.6 81.2 87.5 284.0 6.0 427 3.3 7.0 17.1 2 good 9.0 86.3 111.9 161.2 4.9 282 8.8 20.5 20.9 3 poor 7.7 N /A 70.2 192.7 11.5 279 N /A 3.0 20.4 4 medium 7.1 83.0 95.8 242.2 14.2 81 4.8 7.9 21.4 5 medium 8.3 79.0 78.1 286.7 8.0 539 N /A 1.4 21.4 6 good 9.1 N /A 94.9 185.0 5.9 232 N /A 23.7 18.9 7 medium 7.8 88.0 80.4 325.2 9.2 589 5.7 7.4 24.6 8 medium 7.6 78.4 95.0 177.1 3.2 290 2.5 5.6 13.0 9 good 7.6 N /A 97.8 164.7 4.9 465 N /A 14.5 12.9 Mean SD 8.1 0.7 90.2 12.5 224.3 61.5 7.5 3.6 354 163 10.1 7.8 19.0 4.0 Median 7.8 94.9 192.7 6.0 290.0 7.4 20.4 Pre-HU: parameters before HU initiation; Post-HU: parameters after HU initiation. 3.3. Pharmacokinetic Parameters Principal pharmacokinetic parameters are presented in Table3and mean HU concentration-time are represented in Figure1. The AUC ranged from 43.3 to 113.5 h.mg /L with a median of 75.1 h.mg /L. None of the nine children reached 115 h.mg /L, which was the target-AUC in a study by Dong et al. [21] . Six of them had an AUC less than 100 h.mg /L. However, Patient 2 presented with an AUC of 113.5 h.mg /L and had one of the highest HbF percentages (20.5 %). Patient 6, who had the highest HbF ( =23.7%) , had an AUC of 74.0 h.mg /L, showing a non-optimal response. Every child except one had a time to reach the C max(T max ) between 1 and 2.5 h. Table 3. Pharmacokinetics parameters of the nine children on HU. Patient Treatment Duration (Months) Dose (mg /kg /day) C max(mg /L) T max(hours) AUC (h.mg /L) 1 14.2 17.1 24.0 1.33 75.1 2 121.6 20.9 33.9 1.11 113.5 3 27.3 20.4 14.9 2.00 59.5 4 58.8 21.4 15.2 2.44 57.3 5 138.8 21.4 37.5 1.11 102.0 6 51.6 18.9 25.8 0.66 74.0 7 70.1 24.6 31.0 2.44 108.2 8 11.2 13.0 10.8 1.33 43.3 9 77.8 12.9 24.0 1.33 98.2 Mean Standard Deviation 63.5 ( 44.6) 19.0 ( 4.0) 24.1 ( 9.1) 1.5 ( 0.6) 81.3 ( 25.2) Median 58.8 20.4 24.0 1.33 75.1 Figure 1. Mean HU ( standard deviation) concentration–time plot ( n= 9 patients). 3.4. Optimal Sampling Using a non-compartmental method, a more or less signi cant correlation appears between AUC and the concentrations measured at the same time of sampling. As shown in Figure2a, the most signi cant correlation was obtained at the 2-h sampling time ( r2=0.8775). A less signi cant correlation (Figure2b) was found for the 4-h concentrations ( r2=0.6058). The best correlation was found for the 2-h samples, which could be su cient to predict the patient AUC (Table4).J. Clin. Med. 2019, 8, x FOR PEER REVIEW 5 of 10 4 medium 7.1 8.3 9.1 7.8 7.6 7.6 83.0 95.8 242.2 14.2 81 4.8 7.9 21.4 5 medium 79.0 78.1 286.7 8.0 539 N/A 1.4 21.4 6 good N/A 94.9 185.0 5.9 232 N/A 23.7 18.9 7 medium 88.0 80.4 325.2 9.2 589 5.7 7.4 24.6 8 medium 78.4 95.0 177.1 3.2 290 2.5 5.6 13.0 9 good N/A 97.8 164.7 4.9 465 N/A 14.5 12.9 Mean ± SD 8.1 ± 0.7 90.2 ± 12.5 224.3 ± 61.5 7.5 ± 3.6 354 ± 163 10.1 ± 7.8 19.0 ± 4.0 Median 7.8 94.9 192.7 6.0 290.0 7.4 20.4 Pre-HU: parameters before HU initiation; Post-HU: parameters after HU initiation. 3.3. Pharmacokinetic Parameters Principal pharmacokinetic parameters are presented in Table 3 and mean HU concentration-time are represented in Figure 1. The AUC ranged from 43.3 to 113.5 h.mg/L with a median of 75.1 h.mg/L. None of the nine children reached 115 h.mg/L, which was the target-AUC in a study by Dong et al. [21]. Six of them had an AUC less than 100 h.mg/L. However, Patient 2 presented with an AUC of 113.5 h.mg/L and had one of the highest HbF percentages (20.5 %). Patient 6, who had the highest HbF (= 23.7%), had an AUC of 74.0 h.mg/L, showing a non-optimal response. Every child except one had a time to reach the C max (T max ) between 1 and 2.5 hours. Table 3. Pharmacokinetics parameters of the nine children on HU. Patient Treatment Duration (Months) Dose (mg/kg/day) C max (mg/L) T max (hours) AUC (h.mg/L) 1 14.2 17.1 24.0 1.33 75.1 2 121.6 20.9 33.9 1.11 113.5 3 27.3 20.4 14.9 2.00 59.5 4 58.8 21.4 15.2 2.44 57.3 5 138.8 21.4 37.5 1.11 102.0 6 51.6 18.9 25.8 0.66 74.0 7 70.1 24.6 31.0 2.44 108.2 8 11.2 13.0 10.8 1.33 43.3 9 77.8 12.9 24.0 1.33 98.2 Mean ± Standard Deviation 63.5 (± 44.6) 19.0 (± 4.0) 24.1 (± 9.1) 1.5 (± 0.6) 81.3 (± 25.2) Median 58.8 20.4 24.0 1.33 75.1 Figure 1. Mean HU (± standard deviation) concentration–time plot (n = 9 patients). 3.4. Optimal Sampling Using a non-compartmental method, a more or less significant correlation appears between AUC and the concentrations measured at the same time of sampling. As shown in Figure 2a, the most significant correlation was obtained at the 2-hour sampling time (r 2 = 0.8775). A less significant correlation (Figure 2b) was found for the 4-hour concentrations (r 2 = 0.6058). The best correlation was found for the 2-hour samples, which could be sufficient to predict the patient AUC (Table 4). J. Clin. Med. 2019,8, 1701 6 of 10Figure 2.(a) Relation between area under the curve (AUC) and HU concentration-time for 2-h samples; y=3.5701x +11.727. ( b) Relation between AUC and HU concentration-time for 4-h samples; y = 4.4637x +28.402. Table 4. Determination coe cient r2 for the di erent sampling times. Sampling Time Determination Coe cient r2 0 0.0314 10 min 0.0146 20 min 0.0947 1 h 0.3415 2 h 0.8775 4 h 0.6058 6 h 0.4813 4. Discussion In this study, we analyzed the pharmacokinetic parameters of a population of nine children in order to appreciate the possibility of medical care improvement using PK analysis. This opportunity could allow us to adapt their treatment in a more e cient way. The GC /MS method had the speci city and sensitivity required for the therapeutic follow-up of HU. It was linear from 0.79 to 100 mg /L and had a detection limit of 0.28 mg /L. All these qualities are compatible with the plasma concentrations found in adults and infants [ 25,29]. Even if many HU dosage techniques have been published, only those using mass spectrometry as a detector are speci c enough not to interfere with endogenous compounds and allow low concentration quanti cation [30–32]. Ware et al. described two phenotypic absorption pro les: “Fast” (de ned as C max reached at 15 or 30 min) and “Slow” (C maxreached at 60 or 120 min) [28]. In our study, we also observed a “fast” and “slow” absorption pro le but with C max reached before two hours and after two hours, respectively. This indicates a slower absorption pro le, but six out nine were with “fast” pro les and only three with a “slow” one. Ware et al. described the same proportion between slow and fast pro les despite the time-shift. We highlighted that our patient care is sub-optimal. None of the patients had reached the myelosuppression that was de ned earlier as the MTD. Dong et al., using a Bayesian analysis approach, published that 115 h.mg /L could be chosen as the target AUC to reach at the HU initiation [ 21]. Regarding the pharmacokinetic parameters in our study, none of the patients reached the MTD. Our AUC results were in accordance with observations by Dong et al. before MTD was reached. Moreover, our low AUC results were in accordance with the rst administration of HU found in Ref. [ 21,33]. The highest HbF was 23.7%, while McGann et al. showed that the average HbF of their population was 33.3 9.1% after 12 months of treatment at MTD [33].J. Clin. Med. 2019, 8, x FOR PEER REVIEW 6 of 10 (a) (b) Figure 2. (a) Relation between area under the curve (AUC) and HU concentration-time for 2-hour samples; y = 3.5701x + 11.727. (b) Relation between AUC and HU concentration-time for 4-hour samples; y = 4.4637x + 28.402. Table 4. Determination coefficient r 2 for the different sampling times. Sampling Time Determination Coefficient r 2 0 0.0314 10 min 0.0146 20 min 0.0947 1 hou r 0.3415 2 hours 0.8775 4 hours 0.6058 6 hours 0.4813 4. Discussion In this study, we analyzed the pharmacokinetic parameters of a population of nine children in order to appreciate the possibility of medical care improvement using PK analysis. This opportunity could allow us to adapt their treatment in a more efficient way. The GC/MS method had the specificity and sensitivity required for the therapeutic follow-up of HU. It was linear from 0.79 to 100 mg/L and had a detection limit of 0.28 mg/L. All these qualities are compatible with the plasma concentrations found in adults and infants [25,29]. Even if many HU dosage techniques have been published, only those using mass spectrometry as a detector are specific enough not to interfere with endogenous compounds and allow low concentration quantification [30–32]. Ware et al. described two phenotypic absorption profiles: “Fast” (defined as C max reached at 15 or 30 minutes) and “Slow” (C max reached at 60 or 120 minutes) [28]. In our study, we also observed a “fast” and “slow” absorption profile but with C max reached before two hours and after two hours, respectively. This indicates a slower absorption profile, but six out nine were with “fast” profiles and only three with a “slow” one. Ware et al. described the same proportion between slow and fast profiles despite the time-shift. We highlighted that our patient care is sub-optimal. None of the patients had reached the myelosuppression that was defined earlier as the MTD. Dong et al., using a Bayesian analysis approach, published that 115 h.mg/L could be chosen as the target AUC to reach at the HU initiation [21]. Regarding the pharmacokinetic parameters in our study, none of the patients reached the MTD. Our AUC results were in accordance with observations by Dong et al. before MTD was reached. Moreover, our low AUC results were in accordance with the first administration of HU found in Ref. [21,33]. The highest HbF was 23.7%, while McGann et al. showed that the average HbF of their population was 33.3 ± 9.1% after 12 months of treatment at MTD [33]. r2 = 0.6058 r2 = 0.8775 J. Clin. Med. 2019,8, 1701 7 of 10The rst explanation for our patients not reaching MTD resides in the dose. The administrated doses in our population ranged from 12.9 to 24.6 mg /kg /day, while in the study by Dong et al., when the MTD was reached, doses were between 14.2 and 35.5 mg /kg /day. Despite their long treatment durations (between 11.2 and 138.8 months), we could see that the dose escalation to reach MTD was not done properly for these patients. It is clear that most of the patients did not have the appropriate dose. Secondly, four out of nine children were suspected as non-compliant due to their low or normal MCV; however, using laboratory parameters to assess HU adherence can be misleading since the increased MCV and HbF is not universal [ 23]. Moreover, the genotyping of our population was performed for only one patient, so the association with alpha thalassemia explaining a low MCV cannot be ruled out. MCV prior to HU initiation was not available for all the patients because the treatment was initiated in another country or medical center. Another limitation of our study is the use of patients in order to assess compliance. This method is often unreliable, but some patients admitted their non-adherence. The use of a combination of methods (laboratory parameters, pill counts, logbook) is necessary. Our results are yet consistent with the studies showing the physicians reticence to increase HU dosages and that the adherence of SCA patients to HU is average [23,24]. Another piece of information that has proven its importance is that of the beta haplotypes. Unlike the United States, which has a high predominance of BEN haplotypes, there is a larger proportion of patients with Central African Republic (CAR) haplotypes. It has been shown by Bernaudin et al. that BEN /BEN patients have a better response to HU than CAR /CAR patients [ 34]. Only one result of the haplotype was available, and the patient had a BEN /BEN haplotype. The rest of the population must be explored knowing the in uence on the course of the disease it has. The one pitfall of this study is, of course, the sample size, which was mainly due to the di culty of implementation. In fact, the most restrictive aspect of this method was the number of blood samples needed. Working with a pediatric population, we wanted to nd an optimal sampling time that could predict the exposure to the medication. The best correlation between AUC and HU concentrations was found at two hours. This result is consistent with the literature [ 29,35] and would make PK analysis easier to apply routinely. Furthermore, a recent study (TREAT, ClinicalTrials.gov NCT02286154) demonstrated that the PK guided dose strategy, with a target set at 115 h.mg /L, was more e cient and without excess hematologic toxicities than classical dose escalation based on hematological parameters [33]. This pharmacokinetic approach, o ering no additional toxicities and optimizing the dose of HU more e ciently and quickly, is an important asset in SCA patient care. Reaching MTD will help compliance by helping the patients see the quick bene ts of taking this medication. This is all the more important given the necessity to be e cient before the occurrence of irreversible organ damage. 5. Conclusions It is urgent to be more e cient in the treatment of SCA patients. Speci cally, risks of HU must be compared with the risks of untreated SCA; the natural history of clinically severe SCA is well known with a poor prognosis [ 9,36–38]. We need to stop underusing HU, which has proven its bene ts for years. We have to embrace the concept of dose escalation, and we need to nd ways to be optimal. The PK approach could be one such way. Author Contributions: Conceptualization, C.P. and V.K.; methodology, C.N., A.-N.S., V.K., and C.P.; software, A.-N.S. and G.B.; validation, A.-N.S., G.B., and V.K.; formal analysis, C.N., A.-N.S., V.K., and C.P.; investigation, C.N. and C.P.; resources, J.-M.L.; data curation, C.N., A.-N.S., V.K., and C.P..; writing—original draft preparation, C.N., and C.P.; writing—review and editing, C.N., A.-N.S., V.K., and C.P.; supervision, C.N., A.-N.S., V.K., and C.P.; project administration, J.-M.L. and C.P.; funding acquisition, J.-M.L., V.K., and C.P. Con icts of Interest: The authors declare no con ict of interest. J. Clin. Med. 2019,8, 1701 8 of 10 References 1.Piel, F.B.; Hay, S.I.; Gupta, S.; Weatherall, D.J.; Williams, T.N. Global burden of sickle cell anaemia in children under ve, 2010–2050: Modelling based on demographics, excess mortality, and interventions. PLoS Med. 2013 . [CrossRef] [PubMed] 2. Ware, R.E.; de Montalembert, M.; Tshilolo, L.; Abboud, M.R. Sickle cell disease. 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