Dr Agnieszka Lemanska

Lecturer in Integrated Care
PhD Chemometrics, MSc Pharmacy, PGCert_Teaching
+44 (0)1483 689384
DK 04
Mon - Fri


Areas of specialism

Analysis of routinely collected healthcare data, Cancer survivorship, Patient reported outcomes, Long-term conditions, Multimorbidity

University roles and responsibilities

  • Lead for International, School of Health Sciences
  • Lead for Faculty Staff Mobility, Faculty of Health and Medical Sciences
  • Erasmus Coordinator, School of Health Sciences

My qualifications

PhD Chemometrics
University of Bristol
MSc Pharmacy
Medical University of Warsaw

Affiliations and memberships

General Pharmaceutical Council (GPhC)
Royal Pharmaceutical Society of Great Britain (MRPharmS)
British Oncology Pharmacy Association (BOPA)
National Pharmacy Association
International Population Data Linkage Network

Business, industry and community links

Prostate Cancer UK
Prostate Cancer UK & Movember Foundation


Research interests

Research projects

My teaching

My publications


Lemanska A, Cox A, Kirkby N, Chen T, Faithfull S (2014) Predictive Modelling of Patient Reported Radiotherapy-Related Toxicity by the Application of Symptom Clustering and Autoregression, International Journal of Statistics in Medical Research (3) pp. 412-422
Patient reported outcome measures (PROMs) are increasingly being used in research to explore experiences
of cancer survivors. Techniques to predict symptoms, with the aim of providing triage care, rely on the ability to analyse trends in symptoms or quality of life and at present are limited. The secondary analysis in this study uses a statistical method involving the application of autoregression (AR) to PROMs in order to predict symptom intensity following radiotherapy, and to explore its feasibility as an analytical tool. The technique is demonstrated using an existing dataset of 94 prostate cancer patients who completed a validated battery of PROMs over time. In addition the relationship between symptoms was investigated and symptom clusters were identified to determine their value in assisting predictive modeling. Three symptom clusters, namely urinary, gastrointestinal and emotional were identified. The study indicates that incorporating symptom clustering into predictive modeling helps to identify the most informative predictor variables. The analysis also showed that the degree of rise of symptom intensity during radiotherapy has the ability to predict later radiotherapy-related symptoms. The method was most successful for the prediction of urinary and gastrointestinal symptoms. Quantitative or qualitative prediction was possible on different symptoms. The application of this technique to predict radiotherapy outcomes could lead to increased use of PROMs within clinical practice. This in turn would contribute to improvements in both patient care after radiotherapy and also strategies to prevent side effects. In order to further evaluate the predictive ability of the approach, the analysis of a larger dataset with a longer follow up was identified as the next step.
Lemanska A, Grootveld M, Silwood CJL, Brereton RG (2012) Chemometric variance analysis of 1H NMR metabolomics data on the effects of oral rinse on saliva, Metabolomics 8 pp. 64-80
Saliva is an easy to obtain bodily fluid that is specific to the oral environment. It can be used for metabolomic studies as it is representative of the overall wellbeing of an organism, as well as mouth health and bacterial flora. The metabolomic structure of saliva varies greatly depending on the bacteria present in the mouth as they produce a range of metabolites. In this study we have investigated the metabolomic profiles of human saliva that were obtained using 1H NMR (nuclear magnetic resonance) analysis. 48 samples of saliva were collected from 16 healthy subjects over 3 days. Each sample was split in two and the first half treated with an oral rinse, while the second was left untreated as a control sample. The 96 1H NMR metabolomic profiles obtained in the dataset are affected by three factors, namely 16 subjects, 3 sampling days and 2 treatments. These three factors contribute to the total variation in the dataset. When analysing datasets from saliva using traditional methods such as PCA (principal component analysis), the overall variance is dominated by subjects' contributions, and we cannot see trends that would highlight the effect of specific factors such as oral rinse. In order to identify these trends, we used methods such as MSCA (multilevel simultaneous component analysis) and ASCA (ANOVA simultaneous component analysis), that provide variance splits according to the experimental factors, so that we could look at the particular effect of treatment on saliva. The analysis of the treatment effect was enhanced, as it was isolated from the overall variance and assessed without confounding factors. © 2011 Springer Science+Business Media, LLC.
Faithfull S, Lemanska A, Aslet P, Bhatt N, Coe J, Drudge-Coates L, Feneley M, Glynn-Jones R, Kirby M, Langley S, McNicholas T, Newman J, Smith CC, Sahai A, Trueman E, Payne H (2015) Integrative review on the non-invasive management of lower urinary tract symptoms in men following treatments for pelvic malignancies, INTERNATIONAL JOURNAL OF CLINICAL PRACTICE 69 (10) pp. 1184-1208 WILEY-BLACKWELL
Arber A, Odelius A, Williams P, Lemanska A, Faithfull S (2015) Do patients on oral chemotherapy have sufficient knowledge for optimal adherence? A mixed methods study., European journal of cancer care
A new treatment paradigm has emerged with many patients now receiving oral chemotherapy (OC) as first-line treatment for cancer. Treatment with OC has resulted in reduced hospital costs, more autonomy for patients but with added responsibilities for patient self-management. Little is known about patient's knowledge following patient education to enable optimal adherence with OC. A mixed methods study was carried out using a self-report questionnaire to patients on OC for multiple myeloma (MM) followed by semi-structured interviews with patients at home. Analysis identifies high rates of adherence (92.2%) with OC for MM. However, statistically significant knowledge deficits were identified, which were related to patient ethnicity and to gender. There is the potential for non-intentional non-adherence with OC due to deficits in knowledge of OC. Support at home needs to include primary care practitioners such as GPs, practice nurses and pharmacists so that timely support is easily accessible especially in the early phase of treatment.
Lemanska A, Byford R, Correa A, Cruickshank C, Dearnaley D, Griffin C, Hall E, de Lusignan S, Faithfull S (2017) Linking CHHiP prostate cancer RCT with GP records: A study proposal to investigate the effect of co-morbidities and medications on long-term symptoms and radiotherapy-related toxicity, Technical Innovations & Patient Support in Radiation Oncology 2 pp. 5-12 Elsevier

Patients receiving cancer treatment often have one or more co-morbid conditions that are treated pharmacologically. Co-morbidities are recorded in clinical trials usually only at baseline. However, co-morbidities evolve and new ones emerge during cancer treatment. The interaction between multi-morbidity and cancer recovery is significant but poorly understood.


To investigate the effect of co-morbidities (e.g. cardiovascular and diabetes) and medications (e.g. statins, antihypertensives, metformin) on radiotherapy-related toxicity and long-term symptoms in order to identify potential risk factors. The possible protective effect of medications such as statins or antihypertensives in reducing radiotherapy-related toxicity will also be explored.


Two datasets will be linked. 1) CHHiP (Conventional or Hypofractionated High Dose Intensity Modulated Radiotherapy for Prostate Cancer) randomised control trial. CHHiP contains pelvic symptoms and radiation-related toxicity reported by patients and clinicians. 2) GP (General Practice) data from RCGP RSC (Royal College of General Practitioners Research and Surveillance Centre). The GP records of CHHiP patients will be extracted, including cardiovascular co-morbidities, diabetes and prescription medications. Statistical analysis of the combined dataset will be performed in order to investigate the effect.


Linking two sources of healthcare data is an exciting area of big healthcare data research. With limited data in clinical trials (not all clinical trials collect information on co-morbidities or medications) and limited lengths of follow-up, linking different sources of information is increasingly needed to investigate long-term outcomes. With increasing pressures to collect detailed information in clinical trials (e.g. co-morbidities, medications), linkage to routinely collected data offers the potential to support efficient conduct of clinical trials.

Purpose: To investigate the role of symptom clusters in the analysis and utilisation of Patient-Reported Outcome Measures (PROMs) for data modelling and clinical practice. To compare symptom clusters with scales, and explore their value in PROMs interpretation and symptom management. Methods: A dataset called RT01 (ISCRTN47772397) of 843 prostate cancer patients was used. PROMs were reported with the University of California, Los Angeles Prostate Cancer Index (UCLA-PCI). Symptom clusters were explored with hierarchical cluster analysis (HCA) and average linkage method (correlation >0.6). The reliability of the Urinary Function Scale was evaluated with Cronbach's Alpha. The strength of the relationship between the items was investigated with Spearman's correlation. Predictive accuracy of the clusters was compared to the scales by receiver operating characteristic (ROC) analysis. Presence of urinary symptoms at 3 years measured with the Late Effects on Normal Tissue: Subjective, Objective, Management tool (LENT/SOM) was an endpoint. Results: Two symptom clusters were identified (Urinary Cluster and Sexual Cluster). The grouping of symptom clusters was different than UCLA-PCI Scales. Two items of the Urinary Function Scales (?Number of pads? and ?Urinary leak interfering with sex?) were excluded from the Urinary Cluster. The correlation with the other items in the scale ranged from 0.20-0.21 and 0.31-0.39 respectively. Cronbach's Alpha showed low correlation of those items with the Urinary Function Scale (0.14-0.36 and 0.33-0.44 respectively). All Urinary Function Scale items were subject to a ceiling effect. Clusters had better predictive accuracy, AUC = 0.70-0.65, while scales AUC = 0.67-0.61. Conclusion: This study adds to the knowledge on how cluster analysis can be applied for the interpretation and utilisation of PROMs. We conclude that multiple-item scales should be evaluated and that symptom clusters provide an adaptive and study specific approach for modelling and interpretation of PROMs.
Callwood Alison, Cooke Deborah, Bolger Sarah, Lemanska Agnieszka, Allan Helen (2017) The reliability and validity of multiple mini interviews (MMIs) in values based recruitment to nursing, midwifery and paramedic practice programmes: Findings from an evaluation study, International Journal of Nursing Studies 77 pp. 138-144 Elsevier
Background: Universities in the United Kingdom (UK) are required to incorporate values based recruitment (VBR) into their healthcare student selection processes. This reflects an international drive to strengthen the quality of healthcare service provision. This paper presents novel findings in relation to the reliability and predictive validity of multiple mini interviews (MMIs); one approach to VBR widely being employed by universities.

Objectives: To examine the reliability (internal consistency) and predictive validity of MMIs using end of Year One practice outcomes of under-graduate pre-registration adult, child, mental health nursing, midwifery and paramedic practice students.

Design: Cross-discipline evaluation study. Setting: One university in the United Kingdom.

Participants: Data were collected in two streams: applicants to A) The September 2014 and 2015 Midwifery Studies programmes; B) September 2015 adult; Child and Mental Health Nursing and Paramedic Practice programmes. Fifty-seven midwifery students commenced their programme in 2014 and 69 in 2015; 47 and 54 agreed to participate and completed Year One respectively. 333 healthcare students commenced their programmes in September 2015. Of these, 281 agreed to participate and completed their first year (180 adult, 33 child and 34 mental health nursing and 34 paramedic practice students).

Methods: Stream A featured a seven station four-minute model with one interviewer at each station and in Stream B a six station model was employed. Cronbach?s alpha was used to assess MMI station internal consistency and Pearson?s moment correlation co-efficient to explore associations between participants? admission MMI score and end of Year one clinical practice outcomes (OSCE and mentor grading).


Stream A: Significant correlations are reported between midwifery applicant?s MMI scores and end of Year One practice outcomes. A multivariate linear regression model demonstrated that MMI score significantly predicted end of Year One practice outcomes controlling for age and academic entry level: coefficients 0.195 (p = 0.002) and 0.116 (p = 0.002) for OSCE and mentor grading respectively. In Stream B no significant correlations were found between MMI score and practice outcomes measured by mentor grading.

Internal consistency for each MMI station was ?excellent? with values ranging from 0.966?0.974 across Streams A and B.

Conclusion: This novel, cross-discipline study shows that MMIs are reliable VBR tools which have predictive validity when a seven station model is used. These data are important given the current international use of different MMI models in healthcare student selection processes.

Lemanska Agnieszka, Dearnaley David, Sydes Matthew R, Faithfull Sara (2018) Older age, early symptoms and physical function are associated with the severity of late symptom clusters for men undergoing radiotherapy for prostate cancer, Clinical Oncology 30 (6) pp. 334-345 Elsevier
To identify symptom clusters and predisposing factors associated with long-term symptoms and health-related quality of life (HRQOL) following radiotherapy in men with prostate cancer.

Patient-reported outcomes (PROs) data from the Medical Research Council RT01 radiotherapy with neoadjuvant androgen deprivation therapy (ADT) trial of 843 patients were used. PROs were collected over 5 years with the University of California, Los Angeles Prostate Cancer Index (UCLA-PCI) and the 36-Item Short-Form Health Survey (SF-36). Symptom clusters were explored using hierarchical cluster analysis (HCA). The association of treatment dose, baseline patient characteristics and early symptom clusters with the change in severity of PROs over three years was investigated with multivariate linear mixed effects models.

Seven symptom clusters of three or more symptoms were identified. The clusters were stable over time. The longitudinal profiles of symptom clusters showed the onset of acute symptoms during treatment for all symptom clusters and significant recovery by six months. Some clusters such as Physical Health and Sexual Function were adversely affected more than others by ADT, and were less likely to return to pre-treatment levels over time. Older age was significantly associated with decreased long-term Physical Function, Physical Health and Sexual Function (p

Men with poorer physical function and health prior to or during treatment were more likely to report poorer PROs at year three. Early assessment using PROs and lifestyle interventions should be employed to identify those with higher needs and provide targeted rehabilitation and symptom management.

Poole Karen, Ogden Jane, Gasson Sophie, Lemanska Agnieszka, Archer Fiona, Griffin Bruce, Saxton John, Lyons Karen, Faithfull Sara (2019) Creating a teachable moment in community pharmacy for men with prostate cancer: A qualitative study of lifestyle changes, Psycho-Oncology Wiley


It is well established that exercise and lifestyle behaviours improve men's health outcomes from prostate cancer. With 3.8 million men living with the disease worldwide, the challenge is creating accessible intervention approaches that lead to sustainable lifestyle changes. We carried out a phase II feasibility study of a lifestyle intervention delivered by nine community pharmacies in the United Kingdom to inform a larger efficacy study. Qualitative interviews explored how men experienced the intervention, and these data are presented here.


Community pharmacies delivered a multicomponent lifestyle intervention to 116 men with prostate cancer. The intervention included a health, strength, and fitness assessment, immediate feedback, lifestyle prescription with telephone support, and reassessment 12 weeks later. Three months after receiving the intervention, 33 participants took part in semistructured telephone interviews.


Our framework analysis identified how a teachable moment can be created by a community pharmacy intervention. There was evidence of this when men's self?perception was challenged and coupled to a positive interaction with a pharmacist. Our findings highlight the social context of behaviour change with men identifying how their lifestyle choices were negotiated within their household. There was a ripple effect as lifestyle behaviours made a positive impact on friends and family.


The teachable moment is not a serendipitous opportunity but can be created by an intervention. Our study adds insight into how community pharmacists can support cancer survivors to make positive lifestyle behaviour changes and suggests a role for doing rather than just telling.

Lemanska Agnieszka, Poole Karen, Aning Jonathan J., Griffin Bruce A., Manders Ralph, Saxton John M., Wainwright Joe, Faithfull Sara (2019) The Siconolfi step test: a valid and reliable assessment of cardiopulmonary fitness in older men with prostate cancer, European Review of Aging and Physical Activity 16 (1) pp. 1-10 BMC


Assessing fitness and promoting regular physical activity can improve health outcomes and early recovery in prostate cancer. This is however, underutilised in clinical practice. The cardiopulmonary exercise test (CPET) is increasingly being used pre-treatment to measure aerobic capacity and peak oxygen consumption (VO2peak - a gold standard in cardiopulmonary fitness assessment). However, CPET requires expensive equipment and may not always be appropriate. The Siconolfi step test (SST) is simpler and cheaper, and could provide an alternative.

The aim of this study was to evaluate the validity and reliability of SST for predicting cardiopulmonary fitness in men with prostate cancer. Men were recruited to this two-centre study (Surrey and Newcastle, United Kingdom) after treatment for locally advanced prostate cancer. They had one or more of three risk factors: elevated blood pressure, overweight (BMI Ã 25), or androgen deprivation therapy (ADT). Cardiopulmonary fitness was measured using SST and cycle ergometry CPET, at two visits three months apart. The validity of SST was assessed by comparing it to CPET. The VO2peak predicted from SST was compared to the VO2peak directly measured with CPET. The reliability of SST was assessed by comparing repeated measures. Bland-Altman analysis was used to derive limits of agreement in validity and reliability analysis.


Sixty-six men provided data for both SST and CPET. These data were used for validity analysis. 56 men provided SST data on both visits. These data were used for reliability analysis. SST provided valid prediction of the cardiopulmonary fitness in men à 60 years old. The average difference between CPET and SST was 0.64 ml/kg/min with non-significant positive bias towards CPET (P = 0.217). Bland-Altman 95% limits of agreement of SST with CPET were ± 7.62 ml/kg/min. SST was reliable across the whole age range. Predicted VO2peak was on average 0.53 ml/kg/min higher at Visit 2 than at Visit 1 (P = 0.181). Bland-Altman 95% limits of agreement between repeated SST measures were ± 5.84 ml/kg/min.


SST provides a valid and reliable alternative to CPET for the assessment of cardiopulmonary fitness in older men with prostate cancer. Caution is advised when assessing men 60 years old or younger because the VO2peak predicted with SST was significantly lower than that measured with CPET.