Thirteen-year analyses of medical oncology outpatient day clinic data: a changing field.

Key questions

What is already known about this subject?

Increases in approvals of cancer therapeutics, longer survival, centralisation effects and higher treatment complexity reshape the landscape of medical oncology treatment.

What does this study add?

This study is the first to describe changes of characteristics of a large medical outpatient clinic patient cohort over time.

How might this impact on clinical practice?

Our findings highlight the need to adapt to a novel era of medical oncology, that is defined by increases in patient numbers and visits as well as changes in cancer patient characteristics and entities.

Introduction

Cancer is the second-leading cause of death in industrialised countries. The economic burden of cancer for health insurances and care providers was reported to be increasing in recent years. 1 This observation is attributed to higher prevalence caused by more accurate diagnosis and longer survival of both incurable and hence chronically ill as well as curable patients with cancer. 2 Besides, potential pharmaceutical pricing policies as well as higher life expectancy within the general population and hence years at risk for the development of cancer may contribute to this finding. More accurate and earlier diagnosis was facilitated by the introduction of population-wide screening programmes such as colonoscopy and mammography plans and by creating awareness for cancer in the general population. 3 From a medical oncology point of view, prognosis and survival of cancer patients were ameliorated through the introduction of so-called ‘targeted’ agents, aiming at pharmaceutical inhibition of one specific molecular target, 4 the uprising of immunotherapeutic agents such as immune checkpoint inhibitors 5 and long-year efforts in combining and adopting of cytostatic therapeutic agents to more potent chemotherapy regimens. Besides, closer collaboration efforts with surgical specialties, radiation oncologists 6 and the emergence of supportive care and rehabilitation programmes 7 can be seen as potential reasons for incremental patient survival and quality of life (QOL).

Many cancer entities have seen the approval of numerous new anticancer agents in the last 10 years, not only increasing survival, but also QOL of affected patients. 8 While in many cases these novel drugs are orally available and, in some cases, able to outcompete intravenous chemotherapy, ‘chronification’ of cancer in general leads to a higher burden for healthcare providers and insurance givers globally. 9

As an example, in the entity of breast cancer (BCa) alone, the introduction of the first Her2-targeted therapeutic antibody trastuzumab, has led to an increase in 10-year overall survival rates of early Her2-positive breast cancer from 75% to 84%. 10 The addition of a second antibody targeting Her2 to trastuzumab, pertuzumab, has further increased disease-free survival in this population, 11 as has the addition of trastuzumab-emtansine (TDM-1) for patients not reaching pathological complete response prior to surgery. 12 13 Similar trends can be seen in metastatic BCa, where the approval of CDK4/6 inhibitors in the strictly hormone-dependent or luminal setting, 14 15 again use of trastuzumab and pertuzumab 16 17 as well as TDM-1 18 in Her2-positive BCa and most recently the addition of the immune checkpoint-inhibitor atezolizumab to chemotherapy in triple-negative breast cancer led to higher survival rates in cancer patient populations. 19

In this study, we set to analyse and discuss changes in patient numbers at our academic hospital centre medical oncology outpatient wards and examine changes in prevalence of cancer entities over time. Further, we report short-term outcome measures for our study population and discuss the findings in light of relevant and recent literature.

Methods

Our academic hospital is the largest tertiary healthcare centre in Austria. At our medical oncology department, which comprises of one inpatient ward and one outpatient day clinic, no changes in administrative routine or structures occurred since 2016, when two outpatient day clinics were fused and moved to another floor of the hospital. Tasks performed at the outpatient day clinic include but are not limited to intravenous therapy administration, administration of blood products, treatment of side effects and therapy complications, supportive care measures and performing thoraco- and paracenteses as well as bone marrow biopsies. Of note, patients receiving oral ambulatory therapies are not managed through our outpatient day clinic but through scheduled appointments in our outpatient ambulance and hence not registered in this analysis. Data were collected using our in-house patient administration system (AKIM) for the years 2006–2018 and exported as Microsoft Excel-files. Data for cancer entities and patient transfers/admissions to inpatient wards were available for the time frame of 10 years (2006–2015; 86.787 patient contacts, 6.044 individual patients) only, due to changes in software. Entity data were clustered for visualisation purposes. Data were anonymised and only one master file was kept by the first author. Individual patient determination was made using name and date of birth in order to exclude doublets. Only finalised patient contacts were included. Statistical analyses were performed using Microsoft Excel.

Results

Descriptive results of a large tertiary cancer centre outpatient treatment patient cohort

Our study provides single-centre data on a large patient cohort of outpatient treatment visits over a time frame of 13 years (2006–2018). The total number of patients and patient contacts registered was 9.870 and 125.679, respectively. Mean age of the visiting patient was 59.9 years, with women being younger than men. 55.2% of contacts were accounted for by females, 44.8% by males. This is of interest as 5.149 and 4.271 individual patients registered were female and male respectively, meaning that women had–on average—approximately 1.5 more visits than men (13.5 vs 11.9; table 1 ). This difference was consistent after exclusion of gender-specific cancer entities (13.0 vs 11.8, online supplemental table 1 ).

esmoopen-2020-000880supp001.pdf

Individual patient numbers as well as contacts per patient increase over time

Compared with 2006, the number of individual patients treated at our outpatient ward increased by 45.4% ( figure 1A ; 2006: 1.100; 2018: 1.599). This increase was gradual and consistent through all the years covered by our analysis. Strikingly, the number of patient contacts per year increased to an even greater extent by 63.3% ( figure 1B ;+63.3%; 2006: 8.857; 2018: 14.467) between 2006 and 2018. These findings translated into an increase of outpatient ward contacts per patient by approximately one contact per patient per year ( figure 1C ; 2006: 8.0; 2018: 9.0;+12.4%).

Enhanced patient numbers caused by low-incidence cancer entities

Our department covers the treatment of all major solid tumours as well as selected haematological entities. Data available for the time frame 2006–2015 (86.787 patient contacts, 6.044 individual patients) showed a rise of patient contacts concerning the treatment of the relatively rare cancer entities multiple myeloma and sarcoma, while major entities like breast or gastrointestinal (GI) cancer lost when compared with the previously mentioned overall growth rate of patient contacts of 63.3% ( figure 2A , table 2 ). Of note, myeloma and sarcoma were responsible for 62.2% of the increase seen in patient contacts between 2006 and 2015 ( online supplemental table 2 ).

For entities causing 250–1000 patient contacts at our ward, we saw a decrease of gynaecological and urological cancers, while contacts with less frequent sarcoma patients increased disproportionally ( figure 2B , table 2 ). Entities with fewer than 250 contacts per year showed marked increases for renal, upper GI (gastrointestinal) as well as CNS (central nervous system) cancer patient contacts, having said that yearly variations seemed high ( figure 2C , table 2 ). When looking at historic data from individual patients in 2006 compared with the whole time frame of fully available data, we discovered changes in the composition of our patient collective reproducing the above-mentioned increases in lung cancer and smaller entities, and the relative decrease of patients suffering from breast, colorectal/pancreatic or gynaecological/urological cancers ( figure 2D ).

Low hospitalisation and high release rates indicate excellent safety of outpatient cancer treatment

Of 86.787 patient contacts at our outpatient ward from 2006 to 2015, 841 contacts (1.0%) led to admission to an inpatient ward of our hospital due to poor health status or treatment side effects. Of these patients, about one-third (n=305; 36.3%) were transferred to our own departments’ wards and 23 patients (0.03%) were admitted to an intermediate/intensive care (IMC/ICU) units. No patient died while being admitted to the outpatient ward.

Discussion

Our study represents a large descriptive single-centre analysis of medical oncology outpatient treatment, reporting data from 9.870 individual patients and 125.679 patient contacts. The results show interesting information about the excellent safety profile of ambulatory oncology treatment and an increase in patient numbers and contacts over time, as well as thought-provoking trends concerning changes in the patient population treated. The long time-frame and high patient as well as patient contact numbers are strengths of our study.

The prominent increase in patient contact numbers ( figure 1A, B ) is most likely attributed to centralisation effects on the national as well as international level. While centralisation in oncology can be helpful in ameliorating patient outcomes including survival, as shown by various groups in surgical oncology, 20 21 it causes higher administrative efforts and initial costs for the centres affected by higher patient numbers. This correlates with the established notion, that healthcare provider volume is a predictor of patient outcome for oncological procedures, 22 having said that data for medical oncology procedures such as chemotherapy administration are sparse compared with data reported for surgical procedures. Interestingly, from an administrative point of view, higher costs initially caused for centres affected by higher patient numbers do not outweigh the benefit in cost-effectiveness through centralisation, as described among others by Bristow et al . 23

Moreover, we argue that gaining expertise as well as expert personnel over time for smaller entities additionally augmented centralisation effects within our centre. Offering expert treatment for orphan diseases, such as multiple myeloma, sarcoma or central nervous system tumours, directly influences the patient numbers seen for more underrepresented diseases in any single cancer centre, which in part explains the increases seen for these entities at our department ( figure 2A , table 2 ).

The increase in patient numbers observed for multiple myeloma reflects the high number of newly approved therapeutic substances, their increasing use for this entity and better response/survival. 24 Blimark et al , 25 described a 50% increase of use of bortezomib, thalidomide and/or lenalidomide in the Swedish myeloma registry between 2008 and 2014 (31%–81% as part of first line treatment). Since administration of bortezomib and other novel therapeutics requires parenteral application, patient numbers at treatment administration facilities rise. Interestingly, Blimark et al 25 also highlighted the role of centralisation and treatment in academic cancer centres, with patients treated at such centres exhibiting better survival—confirming observations previously made by Go et al . 26

Concordantly, we argue that approvals of novel cytostatic compounds drive the increase seen for patient visits per year as shown in figure 1C . For some entities, however, availability of novel orally available cytostatic compounds as well as intramuscular and subcutaneous therapies may decrease the number of patients seen at the outpatient day clinic, but increase patient contacts in our ambulance or elsewhere (eg, general practitioners offices). We were not able to register these contacts for this study. Examples for such phenomena could be the replacement of intravenous chemotherapy by CDK4/6 inhibitors for HR-positive/Her2-negative advanced breast cancer, 14 regorafenib or TAS-102 for metastatic colorectal cancer, 27 28 second generation antiandrogens for prostate cancer, 29 30 tyrosine kinase inhibitors for advanced renal 31 32 and EGFR- (Epidermal Growth Factor Receptor)mutated lung cancer 33 or antihormonal agents given through injections—such as somatostatin analogues for neuroendocrine tumours. 34 In some instances, sharp increases and declines of patient contacts were caused by experimental testing of compounds in clinical trials (eg, increase in renal cancer patient contacts through the use of bevacizumab; figure 2C , years 2007–2009). 35

Further, longer patient survival through more lines of therapy received creates an ageing patient population with more treatment-related comorbidities, again causing more complexity and more contacts per individual patient. 36 Interestingly, as shown in table 1 , women had more visits when compared with men. This difference in patient contacts per individual patient between men and women was not driven by gender-specific cancer entities, as it remained stable after their exclusion ( online supplemental table 1 ). This result potentially reflects longer life expectancy and the fact that women show higher adherence to healthcare providers and seek medical consultation more often. 37 38 Whether this is also true for cancer patients receiving chemotherapy at our ward remains unknown, having said that patients visiting our ward are encouraged to visit whenever side effects or complications occur. Behavioural and social 39 as well as biological 40 factors might influence whether patients come early or wait for resolution of symptoms. Furthermore, our study did not correct for types and intervals of treatments administered, which are different between genders. Therefore, we highlight the great need for gender-specific studies further investigating this apparent difference.

Lastly, treatment safety at our outpatient day clinic shows excellent short-term outcome as 1.0% of patient contacts led to patients not leaving the hospital the same day after having received therapy and 0.03% of patient contacts to transfer to IMC/ICU. Data from a smaller study by Markert et al 41 present a similar rate of chemotherapy-related severe adverse events (SAEs) of 0.8% per chemotherapy order, although various methodological differences between the studies and administrational and geographical differences between the centres hinder precise comparison. Please note that admissions at our outpatient day clinics examined are not limited to treatment administration and that endpoints of admission to inpatient ward and rates of SAEs should not be compared. Causes for admissions to inpatient wards, types and severity of adverse events 42 as well as further patient outcomes were not documented or analysed during this study. Also, prescription errors, previously shown to drive SAEs/admissions/readmissions of patients receiving ambulatory chemotherapy, 43 44 could not be assessed. Because of these two weaknesses of our study and due to its retrospective and single-centre design, comparing our outcome results to other centres remains challenging, especially for centres that are not within Europe and might have inferior access to therapies.

Concludingly, our work describes remarkable increases of patient numbers and contacts for ambulatory cancer patients receiving systemic therapy and supportive care measures at one of the largest European academic cancer centres. Interestingly, increases observed were highest for orphan diseases, most likely attributed to centralisation effects. Higher treatment complexity possibly caused by higher number of newly approved therapies and longer survival of patients exhibiting higher rates of treatment-related morbidities resulted in more contacts per patient per year. Of note, more contacts per individual patient were observed for women.

Acknowledgments

The authors would like to acknowledge the great effort of our medical oncology day clinic staff including all nurses, administrative personnel and medical doctors, highlighting the roles of Christine Huspek, Michaela Bauer and Matthias Walter in precise administration of patients. We would also like to thank Dagmar Steinwender for assistance with administrative tasks during finalisation of this project.

Footnotes

Contributors: Conception and design: MM, MP and WL; Development of methodology: MM; Acquisition of data: All authors; Manuscript writing: MM and TT; Interpretation of data and manuscript approval: All authors.

Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests: MM has received honoraria for lectures and consultation from Roche, Novartis, Eli-Lilly and Medmedia and travel support from Amgen, Roche, Novartis, Pierre Fabre, Daiichi Sankyo and Eisai. RB was an advisor for Astra-Zeneca, Celgene, Daiichi, Eisai, Eli-Lilly, MSD, Novartis, Pfizer, Pierre-Fabre, Puma, Roche and Samsung and received lecture honoraria from Accord, Astra-Zeneca, BMS, Celgene, Eli-Lilly, Novartis, Pfizer, Pierre-Fabre, Roche, Sandoz as well as research support from Daiichi, Novartis and Roche. MP has received honoraria for lectures, consultation or advisory board participation from the following for-profit companies: Bayer, Bristol-Myers Squibb, Novartis, Gerson Lehrman Group (GLG), CMC Contrast, GlaxoSmithKline, Mundipharma, Roche, BMJ Journals, MedMedia, Astra Zeneca, AbbVie, Lilly, Medahead, Daiichi Sankyo, Sanofi, Merck Sharp & Dome, Tocagen. The following for-profit companies have supported clinical trials and contracted research conducted by MP with payments made to his institution: Böhringer-Ingelheim, Bristol-Myers Squibb, Roche, Daiichi Sankyo, Merck Sharp & Dome, Novocure, GlaxoSmithKline, AbbVie. ASB has research support from Daiichi Sankyo (≤ €10 000), Roche (> €10 000) and honoraria for lectures, consultation or advisory board participation from Roche Bristol-Meyers Squibb, Merck, Daiichi Sankyo (all <€5000) as well as travel support from Roche, Amgen and AbbVie. TB reports personal fees from Bayer (lecture fee, advisory board), personal fees from PharmaMar (lecture fee, advisory board), personal fees from Eli-Lilly (lecture fee, advisory board) outside the submitted work. SZ-M received honoraria for advisory boards and/or lectures from Boehringer Ingelheim, Merck Sharp & Dohme, Bristol Myers Squibb, Roche, AstraZeneca, Takeda and Pfizer. Research support to her was granted by Merck Sharp & Dohme. TF hast received honoraria from MSD, Merck Darmstadt, Roche, BMS, Accord, Sanofi, Boehringer Ingelheim, Novartis and was and advisor or consultant for MSD; Merck Darmstadt, Amgen, Pfizer, Sanofi and Boehringer Ingelheim. He has further received travel expenses, including accommodations, from Roche, MS and BMS as well as research grants or funding from MSD, Merck Darmstadt. AI-M announces following COIs: Participation at advisory boards of MSD, Servier and BMS, lecture honoraria from Eli Lilly and Servier and travel support from Roche and BMS. She has also served as local PI for clinical trials sponsored by BMS and Astellas. All other authors report no relevant conflicts of interest.

Patient consent for publication: Not required.

Ethics approval: Analyses and data acquisition were approved by our institutional ethics committee (vote number 1131/2020).

Provenance and peer review: Not commissioned; externally peer reviewed.

Data availability statement: Data are available on reasonable request. All data relevant to the study are included in the article or uploaded as online supplemental information. Data consists of retrospective deidentified participant data and remains with the corresponding author.

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Associated Data

Supplementary Materials

esmoopen-2020-000880supp001.pdf