scholarly journals Pemanfaatan Data Transaksi untuk Dasar membangun Strategi berdasarkan Karakteristik Pelanggan dengan Algoritma K-Means Clustering dan Model RFM

2021 ◽  
Vol 7 (1) ◽  
pp. 7-14
Author(s):  
Carudin
Keyword(s):  
Model Cluster ◽  
Cluster 2

Setiap waktu terdapat proses transaksi yang dilakukan oleh pelanggan, proses tersebut menambah koleksi data pada sebuah database. Pada penelitian ini dengan melakukan pemanfaatan data transaksi untuk mengetahui segmentasi pelanggan dan membangun strategi berdasarkan karakteristik pelanggan dengan pendekatan model RFM dan K-Means. K-Means Clustering adalah sebuah algoritma yang dapat menghasilkan suatu model cluster visual dengan aplikasi Rapidminer versi 9.9,  dengan menggunakan atribut RFM berfungsi untuk mewakili jumlah pelanggan dari setiap cluster. Dari data transaksi  3 tahun terakhir 2017, 2018, dan 2019 dengan jumlah  4.332  transaksi yang kemudian diolah berdasarkan model RFM menghasilkan 1898 pelanggan. Selanjutnya dilakukan analisis cluster dengan menggunakan algoritma K-Means dengan hasil cluster 1 memliki 319 pelanggan, cluster 2 memiliki 314 pelanggan, cluster 3 memiliki 316 pelanggan, cluster 4 memiliki 317 pelanggan, cluster 5 memiliki 315 pelanggan, dan cluster 6 memiliki 317 pelanggan. Dari hasil penelitian ini dapat dimanfaatkan oleh perusahaan untuk mengetahui karakteristik pelanggan dan sebagai bahan pertimbangan membuat suatu strategi baru.

scholarly journals Analisis Loyalitas Pelanggan Berbasis Model Recency, Frequency, dan Monetary (RFM) dan Decision Tree pada PT. Solo

2020 ◽  
Vol 7 (5) ◽  
pp. 943
Author(s):  
Basri Basri ◽  
Windu Gata ◽  
Risnandar Risnandar
Keyword(s):  
Decision Tree ◽  
Customer Loyalty ◽  
State Of The Art ◽  
Model Cluster ◽  
Customer Data ◽  
Decision Tree Classification ◽  
Clustering Model ◽  
Rfm Model ◽  
Tree Models ◽  
Cluster 2

<p>Perkembangan bisnis alat tulis kantor dan sekolah saat ini banyak yang menjanjikan, maka banyak bermunculan pemasok baru dalam bisnis Alat Tulis Kantor dan Sekolah (ATKS). PT Solo yang bergerak di bidang bisnis ATKS harus memiliki strategi dalam setiap persaingan usaha, khususnya dalam meraih loyalitas pelanggan. Loyalitas pelanggan sering dipengaruhi oleh faktor jumlah aktivitas transaksi, nilai nominal transaksi, waktu transaksi di perusahaan, dan atribut <em>outlet</em>. Penelitian ini mengusulkan model <em>Recency</em>, <em>Frequency</em>, dan <em>Monetary</em> (RFM) yang dikombinasikan dengan <em>Decision Tree</em>. Model RFM digunakan untuk proses klasterisasi data pelanggan berdasarkan jumlah transaksi, nilai nominal transaksi, waktu transaksi, dan atribut outlet. Sedangkan <em>Decision Tree</em> dapat menggambarkan tingkat loyalitas pelanggan. Data transaksi dalam penelitian ini dilakukan sepanjang 1 Januari hingga 31 Desember 2018 terhadap 1.203 pelanggan dan 18.087 transaki melalui faktur pembelian. Hasil penelitian ini menunjukan bahwa <em>state-of-the-art </em>pada<em> </em>model RFM dan <em>Decision Tree</em> yang diusulkan lebih unggul dibandingkan hanya dengan menggunakan model RFM saja. <em>Cluster</em> ke-1 memiliki 860 pelanggan menghasilkan loyalitas pelanggan sedang (biru), <em>cluster</em> ke-2 memiliki 69 pelanggan menghasilkan loyalitas pelanggan yang tinggi (hijau), dan <em>cluster</em> ke-3 memiliki 274 pelanggan menghasilkan loyalitas pelanggan yang rendah (merah). Model klasterisasi RFM dan klasifikasi <em>Decision Tree </em>telah menghasilkan atribut <em>outlet</em> yang berpengaruh terhadap nilai akurasi sebesar 67,54%.</p><p> </p><p><em><strong>Abstract</strong></em></p><p class="Judul2"> </p><p class="Judul2"><em>The development of office and school stationery business at this time, many promising, so many new suppliers have sprung up in the office and school stationery business. PT Solo, which has the office and school stationery business, must have a strategy in every business competition, especially in achieving customer loyalty. Customer loyalty is often influenced by factors in the number of transaction activities, transaction nominal value, transaction time at the company, and outlet attributes. This research proposes a Recency, Frequency, and Monetary (RFM) model combined with a Decision Tree. RFM model is used to process customer data clustering based on number of transactions, transaction nominal value, transaction time, and outlet attributes. Whereas Decision Tree can describe the level of customer loyalty. Transaction data in this study were conducted from 1 January to 31 December 2018 to the 1,203 customers and 18,087 transactions through purchase invoices. The results of this study indicate that the state-of-the-art in the proposed RFM and Decision Tree models is outperform compared to only using the RFM model. Cluster 1 has 860 customers resulting in moderate customer loyalty (blue), Cluster 2 has 69 customers resulting in high customer loyalty (green), and Cluster 3 has 274 customers resulting in lower customer loyalty (red). RFM clustering model and Decision Tree classification have produced outlet attributes that affect the accuracy value of 67.54%.</em></p><p><em><strong><br /></strong></em></p>

Theoretical study on six-fold coordinated silicon in silicophosphate compounds

2006 ◽  
Vol 84 (8) ◽  
pp. 1024-1030 ◽  
Author(s):  
Hassan Rabaâ ◽  
Fatima Bkiri
Keyword(s):  
Density Functional ◽  
Tight Binding ◽  
High Energy ◽  
Functional Theory ◽  
Model Cluster ◽  
Hartree Fock ◽  
Ir Frequencies ◽  
The Stability ◽  
Remarkable Agreement ◽  
Cluster 2

Extended Hückel tight-binding (EHTB) calculations were performed on silicophosphate compounds with six-coordinated silicon. Speculative structures related to silicon coordination in SiP2O7 are reported. To account for the particular structural distortion caused by the presence of SiO6 in the silicon pyrophosphate, it is important to examine how the stability and the band gap of the extended structure of SiP2O7 are affected. Different theoretical tools are used (EHTB, ab initio Hartree–Fock, and density functional theory DFT-B3LYP). To obtain detailed descriptions of the incorporation of hexacoordinated silicon in this material, the band structures in SiP2O7 and [P2O7]4– were analyzed. It seems that the diffuse orbitals of silicon and the high energy of the Si 3p orbital lead to higher energy coordination and contribute to the breaking of the P-O-P bridge and the forming of a Si-O-P entity in this material. In addition, to provide more evidence of the existence of the octahedral silicon coordination in SiP2O7 (1), two model clusters [P4Si2O23H18] (2) and [P4Si2O19H10] (3) involving silicon atoms in octahedral and tetrahedral sites were investigated using Hartree–Fock and DFT theories. A remarkable agreement between calculated and experimental bond lengths for Si—O and P—O is obtained using the DFT calculation. The model cluster 2 corroborates the structural change in the Si-O-P and P-O-P fragments seen in 1. The IR vibrational frequencies are calculated for both model clusters and are predicted to shift towards lower frequencies in the octahedral Si sites, which is consistent with experimental data.Key words: silicophosphate, SiO6, band structure, tight-binding calculations, Hartree-Fock, DFT, B3LYP, model cluster, IR frequencies.

Heuristische Typologien von Alkoholabhängigen

2011 ◽  
Vol 30 (07) ◽  
pp. 509-516
Author(s):  
K. Bühler
Keyword(s):  
Cluster 2

ZusammenfassungTrotz der Bedeutung biografischer Faktoren für die Alkoholabhängigkeit und Behandlung von Alkoholabhängigen haben wenige Studien biografische Daten von Alkoholabhängigen untersucht. Deshalb wurden in unserer Studie biografische Variablen zusätzlich zu Persönlichkeitsvariablen berücksichtigt. Die Personen wurden clusteranalysiert. Eine 5-Clusterlösung ergab eine gut interpretierbare Klassifikation. Das hinsichtlich des Schweregrades der Störung am wenigsten gestörte Cluster 2 (normovalenter Typ) wurde gefolgt von Cluster 4 (zielgerichtet neurotischer Typ), Cluster 1 (sozionoxischer Typ), Cluster 5 (desorganisiert neurotischer Typ) und Cluster 3 (neurosozionoxischer Typ). Der normovalente Typ ist der signifikant älteste und der neurosozionoxische Typ der signifikant jüngste Typ. Frauen überwiegen in den Typen mit der stärksten Beeinträchtigung, das heißt, im Cluster 3 und 5. Patienten des Clusters 2 entstammen signifikant seltener, Patienten des Clusters 3 hingegen signifikant häufiger unvollständigen Familien. Patienten des Clusters 2 wuchsen signifikant häufiger bei ihren Eltern auf, Patienten des Clusters 3 und 5 hingegen signifikant weniger. Patienten des Clusters 2 und 4 lebten signifikant häufiger in Partnerschaften als die restlichen Cluster. Den entdeckten Typen von Alkoholabhängigen kommt nicht nur eine deskriptive Bedeutung zu, sondern in Anbetracht des unterschiedlichen Schweregrades der Störung auch eine differenzialtherapeutische. Daher wird entsprechend des Schweregrades der Störung eine Differenzialtherapie vorgeschlagen.

Penerapan Data Mining Untuk Prediksi Penjualan Mobil Menggunakan Metode K-Means Clustering

2020 ◽  
Vol 3 (3) ◽  
pp. 187-201
Author(s):  
Sufajar Butsianto ◽  
Nindi Tya Mayangwulan
Keyword(s):  
Data Mining ◽  
Clustering Data ◽  
Cluster 2

Penggunaan mobil di Indonesia setiap tahunnya selalu meningkat dan membuat perusahaan otomotif berlomba-lomba dalam peningkatan penjualannya. Tujuan dari penelitian ini untuk mengelompokan data penjualan kedalam sebuah cluster dengan metode Data Mining Algoritma K-Means Clustering. Data Penjualan nantinya akan dikelompokan berdasarkan kemiripan data tersebut sehingga data dengan karakteristik yang sama akan berada dalam satu cluster. Atribut yang digunakan adalah brand dan penjualan. Cluster yang terbentuk setelah dilakukan proses K-Means Clustering terbagi menjadi tiga cluster yaitu Cluster 0 jumlah anggota 235 dengan presentase 26% dikategorikan Laris, Cluster 1 jumlah anggota 604 dengan presentase 67% dikategorikan Kurang Laris, dan Cluster 2 jumlah angota 61 dengan presentase 7% dikategorikan Paling Laris, dari proses clustering diatas dapat diperoleh validasi DBI (Davies Bouldin Index) dengan nilai 0,341

scholarly journals OP0038 SPLICEOSOME ALTERATIONS IN LEUCOCYTES FROM APS, SLE AND SLE+APS PATIENTS ARE CLOSELY RELATED TO THEIR MAIN CLINICAL FEATURES

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 20.2-20
Author(s):  
A. M. Patiño-Trives ◽  
C. Perez-Sanchez ◽  
A. Ibañez-Costa ◽  
P. S. Laura ◽  
M. Luque-Tévar ◽  
...  
Keyword(s):  
Autoimmune Diseases ◽  
Clinical Features ◽  
Antiphospholipid Syndrome ◽  
Immune Cells ◽  
Inflammatory Mediators ◽  
Clustering Analysis ◽  
Renal Involvement ◽  
Molecular Clustering ◽  
Cluster 2 ◽  
Splicing Machinery

Background:To date, although multiple molecular approaches have illustrated the various aspects of Primary Antiphospholipid Syndrome (APS), systemic lupus erythematosus (SLE) and antiphospholipid syndrome plus lupus (APS plus SLE), no study has so far fully characterized the potential role of posttranscriptional regulatory mechanisms such as the alternative splicing.Objectives:To identify shared and differential changes in the splicing machinery of immune cells from APS, SLE and APS plus SLE patients, and their involvement in the activity and clinical profile of these autoimmune disorders.Methods:Monocytes, lymphocytes and neutrophils from 80 patients (22 APS, 35 SLE and 23 APS plus SLE) and 50 healthy donors (HD) were purified by immunomagnetic selection. Then, selected elements of the splicing machinery were evaluated using a microfluidic qPCR array (Fluidigm). In parallel, extensive clinical/serological evaluation was performed, comprising disease activity, thrombosis and renal involvement, along with autoantibodies, acute phase reactants, complement and inflammatory molecules. Molecular clustering analyses and correlation/association studies were developed.Results:Patients with primary APS, SLE and APS plus SLE displayed significant and specific alterations in the splicing machinery components in comparison with HD, that were further specific for each leukocyte subset. Besides, these alterations were associated with distinctive clinical features.Hence, in APS, clustering analysis allowed to identify two sets of patients representing different molecular profile groups with respect to the expression levels of splicing machinery components. Principal component analyses confirmed a clear separation between patients. Clinically, cluster 1 characterized patients with higher thrombotic episodes and recurrences than cluster 2 and displayed a higher adjusted global APS score (aGAPSS). Accordingly, these patients showed higher levels of inflammatory mediators than cluster 2.Similarly, in patients with APS plus SLE, clustering analysis allowed to identify two sets of patients showing differential expression of splicing machinery components. Clinical and laboratory profiles showed that cluster 2 characterized patients that had suffered more thrombotic recurrences, most of them displaying an aGAPSS over 12 points and expressing higher levels of inflammatory mediators than cluster 1. The incidence of lupus nephropathy was similarly represented in both clusters.Lastly, in SLE patients, molecular clustering analysis identified two sets of patients showing distinctive clinical features. One cluster characterized most of the patients positive for anti-dsDNA antibodies, further suffering lupus nephropathy, and a high proportion of them also presenting atheroma plaques and high levels of inflammatory mediators.Correlation studies further demonstrated that several deranged splicing machinery components in immune cells (i.e. SF3B1tv1, PTBP1, PRP8 and RBM17) were linked to the autoimmune profile of the three autoimmune diseases, albeit in a specific way on each disorder. Accordingly, in vitro treatment of HD lymphocytes with aPL-IgG or anti-dsDNA-IgG changed the expression of spliceosome components also found altered in vivo in the three autoimmune diseases. Finally, the induced over/downregulated expression of selected spliceosome components in leukocytes modulated the expression of inflammatory cytokines, changed the procoagulant/adhesion activities of monocytes and regulated NETosis in neutrophils.Conclusion:1) The splicing machinery, profoundly altered in leukocytes from APS, APS plus SLE and SLE patients, is closely related to the activity of these diseases, their autoimmune and inflammatory profiles. 2) The analysis of the splicing machinery allows the segregation of APS, APS plus SLE and SLE, with specific components explaining the CV risk and renal involvement in these highly related autoimmune disorders.Acknowledgements:Funded by ISCIII, PI18/00837 and RIER RD16/0012/0015 co-funded with FEDERDisclosure of Interests:None declared

scholarly journals Assessment of ecosystem services provided by livestock agroecosystems in the tropics: a case study of tropical island environment of Guadeloupe

2021 ◽  
Vol 53 (4) ◽  
Author(s):  
J.-L. Gourdine ◽  
A. Fourcot ◽  
C. Lefloch ◽  
M. Naves ◽  
G. Alexandre
Keyword(s):  
Ecosystem Services ◽  
Farming System ◽  
Livestock Farming ◽  
Tropical Island ◽  
Cultural Aspects ◽  
Livestock Farming System ◽  
Agroecological Zones ◽  
The Tropics ◽  
Cluster 2

AbstractThe present study aims to assess (1) the ecosystem services (ES) provided by LFS and (2) the differential ES between local (Creole) and exotic breeds from pig, cattle and goat. The ES are defined as the benefits that humans derive from LFS. They were summarized in 12 ES indicators that cover services related to provisioning, ecological and socio-cultural aspects and territorial vitality. A total of 106 LFS units that covers the five agroecological zones of Guadeloupe were analysed. Functional typologies of LFS per species were created from surveys. The effect of breed on the ES indicators was tested. Results showed that the 40 pig LFS units were separated into 3 clusters that were differentiated in ES according to provisioning ES (cluster 1), cultural use and sale to the neighborhood (cluster 2) and pork self-consumption (cluster 3). The typology of the 57 farms with cattle distinguished 4 clusters with differences in ES provided in self-consumption (cluster1), ecological ES (cluster 2), socio-cultural ES for racing or draught oxen (cluster 3) and ES associated with territory vitality (cluster 4). The 66 goat LFS units were classified into 3 clusters different in ES concerning self-consumption (cluster 1), cultural aspects (cluster 2) and provisioning ES (cluster 3). Our study highlights that ES indicators are not breed dependent (P > 0.10) but rather livestock farming system dependent. The ES rely more on the rearing management than on the breed type, and up to now, there are no specifications in Guadeloupe to differentiate management between breeds.

scholarly journals MBRS-69. METABOLITE PROFILING OF SHH MEDULLOBLASTOMA IDENTIFIES A SUBSET OF CHILDHOOD TUMOURS ENRICHED FOR HIGH-RISK MOLECULAR BIOMARKERS AND CLINICAL FEATURES

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii410-iii410
Author(s):  
Christopher Bennett ◽  
Sarah Kohe ◽  
Florence Burte ◽  
Heather Rose ◽  
Debbie Hicks ◽  
...  
Keyword(s):  
High Risk ◽  
Metabolite Profiling ◽  
Unmet Need ◽  
Magic Angle Spinning ◽  
Molecular Biomarkers ◽  
Mycn Amplification ◽  
Resonance Spectroscopy ◽  
Magic Angle ◽  
Metabolite Profiles ◽  
Cluster 2

Abstract SHH medulloblastoma patients have a variable prognosis. Infants (&lt;3–5 years at diagnosis) are associated with a good prognosis, while disease-course in childhood is associated with specific prognostic biomarkers (MYCN amplification, TP53 mutation, LCA histology; all high-risk). There is an unmet need to identify prognostic subgroups of SHH tumours rapidly in the clinical setting, to aid in real-time risk stratification and disease management. Metabolite profiling is a powerful technique for characterising tumours. High resolution magic angle spinning NMR spectroscopy (HR-MAS) can be performed on frozen tissue samples and provides high quality metabolite information. We therefore assessed whether metabolite profiles could identify subsets of SHH tumours with prognostic potential. Metabolite concentrations of 22 SHH tumours were acquired by HR-MAS and analysed using unsupervised hierarchical clustering. Methylation profiling assigned the infant and childhood SHH subtypes, and clinical and molecular features were compared between clusters. Two clusters were observed. A significantly higher concentration of lipids was observed in Cluster 1 (t-test, p=0.012). Cluster 1 consisted entirely of childhood-SHH whilst Cluster 2 included both childhood-SHH and infant-SHH subtypes. Cluster 1 was enriched for high-risk markers - LCA histology (3/7 v. 0/5), MYCN amplification (2/7 v. 0/5), TP53 mutations (3/7 v. 1/5) and metastatic disease - whilst having a lower proportion of TERT mutations (0/7 v. 2/5) than Cluster 2. These pilot results suggest that (i) it is possible to identify childhood-SHH patients linked to high-risk clinical and molecular biomarkers using metabolite profiles and (ii) these may be detected non-invasively in vivo using magnetic-resonance spectroscopy.

scholarly journals Echocardiographic phenotypes of patients with sickle cell disease. An unsupervised analysis based on etendard cohort

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
T D"humieres ◽  
J Inamo ◽  
S Deswarte ◽  
T Damy ◽  
G Loko ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Cardiac Output ◽  
Sickle Cell Disease ◽  
Diastolic Function ◽  
Sickle Cell ◽  
Left Ventricular ◽  
Integrative Approach ◽  
Cell Disease ◽  
Clinical Profiles ◽  
Cluster 2

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): PHRC Backgroung Echocardiography is the cornerstone in the diagnosis of cardiopulmonary involvement in sickle cell disease (SCD). However, given the unique pathophysiology of SCD associating high cardiac output, and various degrees of peripheral vasculopathy, differentiate the pathological from the physiological using echocardiography can be particularly challenging. Purpose This study sought to link cardiac phenotypes in homozygous SCD patients with clinical profiles and outcomes using cluster analysis. Methods We analyzed data of 379 patients with a sufficient echographic dataset included in the French Etendard Cohort, a prospective cohort initially designed to assess the prevalence of pulmonary hypertension. A cluster analysis was performed on echocardiographic variables, and the association between clusters and clinical profiles and outcomes was assessed. Results Three clusters were identified. Cluster 1 (N = 122) patients had the lowest cardiac output, only mild left cavities remodeling, diastolic dysfunction, and high tricuspid regurgitation velocity (TRV). They were predominantly female, as old as cluster 2, and displayed the most severe functional limitation. Cluster 2 (N = 103) patients had the highest cardiac output, left ventricular mass and a severely dilated left atrium. Diastolic function and TRV were similar to cluster 1. These patients had a higher blood pressure and a severe hemolytic anemia. Cluster 3 (N = 154) patients had mild left cavities remodeling, the best diastolic function and the lowest TRV. They were younger patients with the highest hemoglobin and lowest hemolytic markers. Right heart catheterization was performed in 94 patients. Cluster 1 gathered the majority of precapillary PH while cluster 2 gathered postcapillary PH and no PH was found in cluster 3. After a follow-up of 9.9 years (IQR: 9.3 to 10.5 years) death occurred in 38 patients (10%). Clusters 2 had the worst prognosis with 18% mortality rate vs. 12% in cluster 2 and 5% in cluster 1 (P log-rank = 0,02). Results are summarized in the central illustration. Conclusions Cluster analysis of echocardiographic variables identified 3 phenotypes among SCD patients, each associated with different clinical features and outcome. These findings underlines the necessity to rethink echocardiographic evaluation of SCD patients, with an integrative approach based on simultaneous evaluation of TRV along with left cavities remodeling and diastolic parameters. Abstract Figure.

scholarly journals Pattern of inflammatory immune response determines the clinical course and outcome of COVID-19: unbiased clustering analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eunyoung Emily Lee ◽  
Kyoung-Ho Song ◽  
Woochang Hwang ◽  
Sin Young Ham ◽  
Hyeonju Jeong ◽  
...  
Keyword(s):  
Immune Response ◽  
Immune Responses ◽  
Clustering Analysis ◽  
Validation Cohort ◽  
Inflammatory Responses ◽  
Clinical Course ◽  
Severe Disease ◽  
Outcome Data ◽  
Inflammatory Immune Response ◽  
Cluster 2

AbstractThe objective of the study was to identify distinct patterns in inflammatory immune responses of COVID-19 patients and to investigate their association with clinical course and outcome. Data from hospitalized COVID-19 patients were retrieved from electronic medical record. Supervised k-means clustering of serial C-reactive protein levels (CRP), absolute neutrophil counts (ANC), and absolute lymphocyte counts (ALC) was used to assign immune responses to one of three groups. Then, relationships between patterns of inflammatory responses and clinical course and outcome of COVID-19 were assessed in a discovery and validation cohort. Unbiased clustering analysis grouped 105 patients of a discovery cohort into three distinct clusters. Cluster 1 (hyper-inflammatory immune response) was characterized by high CRP levels, high ANC, and low ALC, whereas Cluster 3 (hypo-inflammatory immune response) was associated with low CRP levels and normal ANC and ALC. Cluster 2 showed an intermediate pattern. All patients in Cluster 1 required oxygen support whilst 61% patients in Cluster 2 and no patient in Cluster 3 required supplementary oxygen. Two (13.3%) patients in Cluster 1 died, whereas no patient in Clusters 2 and 3 died. The results were confirmed in an independent validation cohort of 116 patients. We identified three different patterns of inflammatory immune response to COVID-19. Hyper-inflammatory immune responses with elevated CRP, neutrophilia, and lymphopenia are associated with a severe disease and a worse outcome. Therefore, targeting the hyper-inflammatory response might improve the clinical outcome of COVID-19.

scholarly journals Symptom clusters and their influence on prognosis using EORTC QLQ-C15-PAL scores in terminally ill patients with cancer

2021 ◽  
Author(s):  
Nanako Koyama ◽  
Chikako Matsumura ◽  
Yuuna Tahara ◽  
Morito Sako ◽  
Hideo Kurosawa ◽  
...  
Keyword(s):  
Palliative Care ◽  
Terminally Ill ◽  
Symptom Clusters ◽  
Rank Test ◽  
Appetite Loss ◽  
Patients With Cancer ◽  
Terminally Ill Patients ◽  
Log Rank Test ◽  
Eortc Qlq ◽  
Cluster 2

Abstract Purpose The aims of the present study were to investigate the symptom clusters in terminally ill patients with cancer using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 15 Palliative Care (EORTC QLQ-C15-PAL), and to examine whether these symptom clusters influenced prognosis. Methods We analyzed data from 130 cancer patients hospitalized in the palliative care unit from June 2018 to December 2019 in an observational study. Principal component analysis was used to detect symptom clusters using the scored date of 14 items in the QLQ-C15-PAL, except for overall QOL, at the time of hospitalization. The influence of the existence of these symptom clusters and Palliative Performance Scale (PPS) on survival was analyzed by Cox proportional hazards regression analysis, and survival curves were compared between the groups with or without existing corresponding symptom clusters using the log-rank test. Results The following symptom clusters were identified: cluster 1 (pain, insomnia, emotional functioning), cluster 2 (dyspnea, appetite loss, fatigue, and nausea), and cluster 3 (physical functioning). Cronbach’s alpha values for the symptom clusters ranged from 0.72 to 0.82. An increased risk of death was significantly associated with the existence of cluster 2 and poor PPS (log-rank test, p = 0.016 and p < 0.001, respectively). Conclusion In terminally ill patients with cancer, three symptom clusters were detected based on QLQ-C15-PAL scores. Poor PPS and the presence of symptom cluster that includes dyspnea, appetite loss, fatigue, and nausea indicated poor prognosis.

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