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Annals of Oncology
Annals of Oncology 26: 1325–1332, 2015 doi:10.1093/annonc/mdv025 Published online 20 January 2015
Consideration of comorbidity in treatment decision making in multidisciplinary cancer team meetings: a systematic review J. Stairmand1, L. Signal1*, D. Sarfati1, C. Jackson2, L. Batten3, M. Holdaway3 & C. Cunningham3 1 Cancer Control and Screening Research Group, University of Otago, Wellington; 2Department of Medicine, University of Otago, Dunedin; 3Research Centre for Ma¯ori Health and Development, Massey University, Palmerston North, New Zealand
Received 20 September 2014; revised 24 November 2014 and 16 December 2014; accepted 17 December 2014
Background: Comorbidity is very common among patients with cancer. Multidisciplinary team meetings (MDTs) are increasingly the context within which cancer treatment decisions are made internationally. Little is known about how comorbidity is considered, or impacts decisions, in MDTs. Methods: A systematic literature review was conducted to evaluate previous evidence on consideration, and impact, of comorbidity in cancer MDT treatment decision making. Twenty-one original studies were included. Results: Lack of information on comorbidity in MDTs impedes the ability of MDT members to make treatment recommendations, and for those recommendations to be implemented among patients with comorbidity. Where treatment is different from that recommended due to comorbidity, it is more conservative, despite evidence that such treatment may be tolerated and effective. MDT members are likely to be unaware of the extent to which issues such as comorbidity are ignored. Conclusions: MDTs should systematically consider treatment of patients with comorbidity. Further research is needed to assist clinicians to undertake MDT decision making that appropriately addresses comorbidity. If this were to occur, it would likely contribute to improved outcomes for cancer patients with comorbidities. Key words: cancer, comorbidity, decision making, multidisciplinary team meetings, systematic review
introduction Comorbidity is very common among patients with cancer and its consequences pose a major clinical challenge in the treatment of cancer. As comorbidities may adversely affect an individual’s access to, and the effectiveness of, major cancer treatments, it is also a significant prognostic factor for long-term survival from cancer [1–3]. Comorbidity acts on survival both through direct mechanisms related to the increased physiological burden of disease, and through indirect mechanisms related to the effects comorbidity has on treatment choice, timeliness and/or effectiveness. Cancer patients with comorbidity are considerably less likely to be offered active therapy [4–6]. However, there is growing evidence that such treatments can be both tolerated and effective by some patients with comorbidity [5, 7–10]. Internationally, multidisciplinary team meetings (MDTs) are increasingly the context within which cancer treatment decisions are made. In the literature, MDTs are referred to using a number of terms e.g. tumour boards, tumour meetings and multidisciplinary cancer team meetings. In this paper, we use the
*Correspondence to: Dr. Louise Signal, Cancer Control and Screening Research Group, University of Otago, PO Box 7343, Wellington South, Wellington 6242, New Zealand. Tel: +64-4-385-5541; Fax: +64-4-389-5319; E-mail: [email protected]
term MDT for consistency to refer to a ‘group of people of different healthcare disciplines, which meets together at a given time (whether physically in one place, or by video or teleconferencing) to discuss a given patient and who are each able to contribute independently to the diagnostic and treatment decisions about the patient’ [11]. MDTs are often highly pressurized, with high caseloads, little time to process highly technical information, and frequently have members absent [12–14]. Nevertheless, there is growing evidence that MDTs are associated with ‘improved clinical decision making, clinical outcomes, patient experience, and the working lives of team members’ [12]. Efforts are being made to find ways to strengthen MDT functioning [15]. Little is known about how comorbidity impacts decisions in cancer MDTs. The aim of this systematic review is to summarize and evaluate previous evidence on consideration, and impact, of comorbidity in cancer MDT treatment decision making and to make suggestions for future practice and research.
materials and methods Studies that reported the findings of original research which met the following criteria were included in this review: (i) published from January 2005 to May 2014 and in English in peer-reviewed journals, (ii) investigated MDT treatment decision making as a
© The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: [email protected].
reviews primary or secondary objective, (iii) the MDT was focused on addressing a certain type, or types, of cancer, (iv) the studies addressed comorbidity. The studies were identified using a systematic search of electronic databases, including Medline, CINAHL, Cochrane CENTRAL and Embase. The reference lists of retrieved articles included in the review were hand-searched and advice sought from experts in the field. Broad search terms were used to ensure all relevant articles were identified. The databases were searched with combinations of terms and variations of the following: ‘decision making’, ‘multidisciplinary team’, ‘neoplasm’ and ‘comorbidity’ (full details of the search strategy can be found in supplementary S1, available at Annals of Oncology online). The studies included were categorized and evaluated by three authors (JS, DS and LS). Methodological evaluation was based on previously established criteria [16]. Findings were synthesized using narrative summary.
results A total of 659 articles were retrieved. Application of the inclusion criteria excluded 638 articles. Excluded articles did not consider comorbidity (see Figure 1 and supplementary S1, available at Annals of Oncology online, for details). The 21 articles reviewed were published between 2006 and 2014. The outcomes in the articles assessed were heterogeneous; thus, a meta-analytic approach was not possible. Of the 21 studies, 15 were quantitative [15, 17–30], and 6 were qualitative [14, 31–35]. Key characteristics of the papers are presented in Table 1. The data sources were information obtained from medical records (n = 13) [17–22, 24–30], surveys (n = 2) [15, 23], routine data (n = 1) [24], observation (n = 2) [14, 15], semi-structured interviews (n = 5) [14, 31, 32, 34, 35], focus group [33] and ethnography [31]. Papers were from UK (n = 12) [14, 15, 17, 20, 21,
• 659 Titles from search Search
• 659 Titles reviewed against inclusion criteria • 72 Titles excluded Titles
Abstracts
Full text articles
Articles for analysis
• 587 Abstracts reviewed • 494 Abstracts excluded
• 93 Full text articles reviewed • 72 Full text articles excluded
• 21 Full text articles included
Figure 1. Article inclusion flow diagram.
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23, 29–32, 34, 35], Australia (n = 3) [18, 19, 33], China [22], USA [24], Germany [26], France (n = 2) [27, 28] and Sweden [25]. Eleven MDT areas of specialty were represented in the original articles: gastrointestinal (n = 2) [17, 34], colorectal (n = 2) [20, 27], lung (n = 2) [18, 19], gynaecology (n = 2) [14, 31], breast (n = 4) [21, 22, 28, 30], head and neck [25], oesophageal [26], thoracic [24], prostate [29], urology (n = 2) [34, 35] and four unspecified [15, 23, 32, 33]. The MDT care studied was centred across UK cancer networks and hospitals (n = 10) [15, 17, 20, 21, 29–32, 34, 35], an Australian cancer therapy centre (n = 2) [18, 19] and hospital [33], hospitals in Hong Kong [22], France (n = 2) [27, 28], Sweden [25], Germany [26] and a Cancer Institute in Tennessee [24]. Fourteen studies looked at patient cases where MDT decisions had been made [15, 17–22, 24–30] and eight involved participants in MDTs [14, 15, 23, 31–35]. A summary of the findings is presented below for each of the thematic areas of interest.
is comorbidity considered in MDTs? There were a number of studies that noted that comorbidity was not well considered in MDTs [14, 15, 23, 29, 32, 34, 35]. Kidger et al. [14] undertook observations of MDTs and interviews with MDT team members in the UK. They found that comorbidity was not routinely presented or discussed unless an MDT participant identified it as having the potential to influence treatment decisions, or when a patient was in particularly poor health. MDT participants had varying opinions about the presentation of comorbidity with some suggesting that it was included as necessary while others thought it needed more attention and could be systematically included [14]. Two other recent studies involving interviews with MDT members found that participants reported that insufficient information on comorbidity was a barrier to decision making [34, 35]. In the UK, Lamb et al. [15] observed MDT meetings and MDT members completed a self-assessment survey. The authors found that comorbidities were not well covered and that team members tended to overrate aspects of their performance, including their consideration of comorbidities. Two other studies noted that comorbidity was not always considered appropriately in MDTs [23, 32]. Kastner et al. [29] aimed to determine whether a particular measure of comorbidity (the Charlson Comorbidity Index) [36] would be a useful addition in the context of a prostate cancer MDT. Based on their finding that, a patient Charlson Comorbidity Index was associated with survival, they concluded that they should adopt this approach to explicitly considering comorbidity in their MDT.
impact of comorbidity on MDT decisions There is evidence in the literature that information on comorbidity (or lack of it) has three implications for MDT decision making. First, MDT decisions are less likely to be made for patients with comorbidity. Three studies [25, 32, 33] found that lack of information on comorbidity was a barrier to reaching a clear treatment plan. Similarly, Kidger et al. [14] noted that, when treatment decisions were not made, this was due to the complexity of the case and the extent of agreement among team members. Clearly, comorbidity could be a reason for such complexity.
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Study question
Main outcome
Sample
Design
Data collection
Barthélémy et al. [28]
France
Elderly patients were less likely to receive adjuvant chemotherapy even when deemed appropriate by guidelines (P < 0.001).
n = 192 decisions
Quantitative
Medical records
Blazeby et al. [17]
UK
What is the impact of age, geriatric assessment and other variables on recommendations by tumour boards for adjuvant chemotherapy in elderly breast cancer patients? Are upper GI MDT decisions implemented?
n = 271 decisions
Quantitative
Medical records
Bumm et al. [26]
Germany
What is the feasibility of a daily tumour MDT in a high-volume university hospital?
OC n = 1238 patients GC n = 1212 patients
Quantitative
Medical records
Chan et al. [22]
China
n = 563 patients
Quantitative
Medical records
Devitt et al. [33]
Australia
What is the applicability of the multidisciplinary approach to the management of breast cancer? What are the views of health professionals attending MDTs of decision making processes and meeting dynamics?
n = 4 focus groups n = 23 participants
Qualitative
Focus group
English et al. [21]
UK
Are breast cancer MDT decisions implemented and what factors influence these processes?
n = 289 decisions n = 210 women
Quantitative
Medical records
Jalil et al. [34]
UK
What are the factors influencing decision making and decision implementation in cancer MDTs?
n = 22 team members
Qualitative
Semi-structured interviews
Kastner et al. [29]
UK
What is the feasibility of using the Charlson Comorbidity Index (CCI) in MDT planning of the treatment of patients with prostate cancer?
15.1% (95% CI 11.1% to 20%) of MDT decisions were not implemented. Reasons for discordance included comorbidity (43.9%). Nonimplementation often resulted in more conservative treatment than originally planned. Comorbidities such as obesity (using BMI) for patients with oesophageal carcinoma (OC) and stress for patients with OC and gastric cancer (GC) are considered by the MDT when evaluating patients’ perioperative risk. Adjuvant treatment was not recommended by the multidisciplinary conference panel for 29 patients owing to old age or concomitant medical illness. Psychosocial concerns of patients were often neglected and at times inadequate information on patients’ comorbid conditions constrained treatment recommendations. 6.9% (95% CI 4.3% to 10.5%) of MDT decisions were not implemented. Reasons for changes to MDT decision were patient preferences (65%), new clinical information (15%) and doctor’s view (20%). Barriers to clinical decision making included: inadequate clinical information; lack of investigation results; non-attendance of key members; teleconferencing failures. Barriers to implementation of MDT recommendations included: non-consideration of patients’ choices or comorbidities; disease progression at the time of implementation. The CCI was a statistically significant predictor of survival, following radical treatment of localized prostate cancer (P = 0.005). The CCI was easy to calculate and therefore feasible to use in the MDT setting.
n = 37 decisions
Quantitative
Medical records
Continued
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Table 1. Characteristics of papers included Study
Country
Study question
Main outcome
Sample
Design
Data collection
Kidger et al. [14]
UK
What factors influence treatment decision making in a gynaecological cancer MDT?
n = 1 MDT n = 16 team members
Qualitative
Meeting observation and semi-structured interviews
Kurtz et al. [27]
France
Does age negatively impact on adjuvant chemotherapy in colorectal MDT decisions?
n = 193 decisions
Quantitative
Medical records
Lamb et al. [32]
UK
What are the attitudes of MDT members; what are the barriers and facilitators for effective teamwork; and what do MDT members consider best practice?
n = 19 MDT members
Qualitative
Semi-structured interviews
Lamb et al. [23]
UK
n = 61 responses
Quantitative
Survey
Lamb et al. [15]
UK
What contribution do oncologists make to MDTs; what is their experience of leadership in MDTs and are they potential MDT leaders? What quality of information is presented by MDT members and who contributes to decision making? Is there correlation between observational and self-reported metrics?
n = 164 cases n = 47 surveys n = 5 MDTs n = 67 team members
Quantitative
Observational tools and on-line selfassessment survey
Lanceley et al. [31]
UK
Patient-centred factors, such as comorbidity, were more peripheral and not routinely discussed. This was partly due to members’ type and level of participation: senior clinicians occupied the most dominant roles whereas nurses contributed less. Disease stage was the major variable leading to adjuvant treatment recommendation, age and comorbidities were of lesser importance. Elderly colorectal cancer patients were not undertreated. Ten respondents agreed that comorbidities (psychological and social problems) were adequately presented. Lack of information on comorbidities was identified by three respondents as a barrier to reaching a clear treatment plan at MDTs. 92% of respondents felt their MDT venue was fit for purpose. Information about patient comorbidities were less likely to be presented in MDTs when their venue was not fit for purpose (P < 0.05, χ 2). Quality of information presented: patient views and comorbidities/psychosocial issues rated lowest. A pronounced difference between expert observer rating and MDT member self-rating was found for the quality of patient-centred information (comorbidities, psychosocial issues, and patients’ views) presented to the team. Contribution to decision making: surgeons and oncologists rated highest and nurses and MDT coordinators lowest. There are three major influences: discussions are dominated by those with medical, surgical or diagnostic expertise; compliance with policy initiatives concerning diagnosis and treatment; and if the patient is known or not by members of the MDT. It was difficult for non-medical team members to contribute to the meeting even when patients had differing characteristics e.g. physical comorbidity.
n = 53 MDT participants
Qualitative
Ethnography, ethnographic field notes, semistructured interviews
What influences clinical decisions made in a gynaecological cancer MDT?
Annals of Oncology
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Table 1. Continued
What is the benefit of multidisciplinary thoracic oncology MDTs? When care deviates from that recommended what is the impact on patient outcomes? To evaluate the implementation of MDT decisions for patients with breast cancer in a modern breast unit.
Rajan et al. [30]
UK
Sarkar et al. [35]
UK
To explore current practices in urology MDT meeting organization, case preparation and the potential for case selection from the perspective of team members.
Stalfors et al. [25]
Sweden
What is the quality and efficacy of the head and neck oncology MDT?
Vinod et al. [18]
Australia
Are MDT recommendations concordant with guidelines in the treatment of lung cancer?
Vinod et al. [19]
Australia
What are the reasons for lung cancer patients receiving no treatment?
Wood et al. [20]
UK
Are colorectal MDT decisions implemented? And if not why?
235 patients received concordant care and 141 did not. Comorbidity in 14 of 104 instances was identified as a reason for clinician-induced discordance of care. The vast majority of MDT decisions are implemented. Management alteration was most often due to patient choice or additional information available including that related to comorbidity after the MDT. A minority of management alterations were ‘unjustifiable’. Factors negatively influencing the MDTs included insufficient time to prepare cases so that enough information is available to make appropriate decisions: absence of the clinician in charge or not knowing the patient; and lack of a systematic approach to case discussion. Participants recommended improvements including protected time for case preparation and focusing on patient comorbidities. Uncertainty regarding general cardiovascular status (6%) resulted in the inability to establish a diagnosis and treatment plans. 16% of these failures required complementary information. Concordance with guidelines existed in 58% of surgical cases, 88% of radiotherapy cases and 77% of chemotherapy cases. Reasons for MDT not recommending guideline treatment included comorbidity (25%). Guidelines recommended no treatment in 4% of cases compared with 10% by MDT. Differences were due to comorbidities and clinician decision. 20% of patients actually received no treatment. The majority of decisions were implemented. 10% (95% CI 6.3–15.2) were not. Reasons for nonimplementation included comorbidity (40%) resulting in more conservative treatment than planned.
n = 376 patients n = 454 recommendations
Quantitative
Medical records and Social Security Death Index
n = 705 patients n = 3230 MDT decisions
Quantitative
Medical records
n = 20 MDT participants
Qualitative
Semi-structured interviews
n = 324 patients
Quantitative
Medical records
n = 335 patients
Quantitative
Medical records
n = 335 patients
Quantitative
Medical records
n = 201 treatment decisions n = 157 patients
Quantitative
Medical records
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Osarogiagbon et al. [24]
reviews Second, decisions made for patients with comorbidity are less likely to be concordant with clinical guidelines. Vinod et al. [18, 19] found that 29% of lung cancer patients reviewed in MDTs received care outside of that recommended in the guidelines, and comorbidity was given as the reason for the disparity in a quarter of these [18]. Further, although the guideline recommended no treatment in 4% of patients, MDTs recommended no treatment in 10% [19]. Again, a key reason for the discrepancy was comorbidity (47%). Patients with at least one comorbid condition were more likely to have no treatment (24%) than those who did not have any such conditions (12%) (P = 0.005) [19]. Consistent with these findings, Kurtz et al. [27] assessed the extent to which treatment recommendations from MDTs within a single institute were consistent with guidelines. They found that both comorbidity and ‘old age’ were frequently cited causes for discordant treatment. Similarly, Chan et al. [22] found that comorbidity was cited as a reason for not recommending adjuvant treatment. In contrast, Barthélémy et al. [28] assessed whether recommendations for adjuvant chemotherapy for elderly patients with breast cancer were associated with categorization according to the Comprehensive Geriatric Assessment (which includes an assessment of comorbidity) and found little association. However, when patients did not receive recommended chemotherapy, age and comorbidity were still often cited as reasons. Third, that even when treatment decisions are reached in MDTs, the actual treatment received is more likely to be discordant with that decision among patients with comorbidity. Several studies investigated reasons why MDT decisions were not implemented [17, 20–22, 24, 27, 28, 30, 34]. All but one [21] found comorbidity was an important reason for this discordance. Of the eight studies that found comorbidity was a reason for not implementing decisions [17, 20, 22, 24, 27, 28, 30, 34], seven were reviews of medical records [17, 20, 22, 24, 27, 28, 30] and one a report of MDT participants’ perspectives [34]. When decisions were changed post-MDT, as a result of new information about comorbidity, they resulted in more conservative treatment [17, 20].
discussion To the best of our knowledge, this is the first review to assess consideration of comorbidity, and its impact, in cancer MDT decision making. We found a limited number of articles which examined comorbidity. The review results suggest that comorbidity is not well considered in MDTs [14, 15, 23, 29, 32, 34, 35]. MDTs are less likely to make treatment recommendations for patients with comorbidity [14, 25, 33] and, when recommendations are made, comorbidity appears to be a key reason for MDTs not making these in line with guidelines [18, 19, 22, 27, 28]. Further, when recommendations are made, comorbidity is a key reason for not implementing these [17, 20, 22, 24, 27, 28, 30, 34]. The evidence relating to the potential benefits and harms of cancer treatments among patients with comorbidity is scarce, not least of all because patients with comorbidity are often excluded from relevant randomized controlled trials [37, 38]. Consistent with the findings of this review, a number of vignette-based studies have found that surgeons and oncologists
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are less likely to refer or recommend treatment of cancer patients with comorbidity [39–41]. Clinicians may be concerned about potential toxicity or effectiveness of treatments among those with comorbidity, and/or may consider that some patients’ life expectancy is too short to justify the risks of treatment. In fact, research relating to the risk of complications and effectiveness of cancer treatment in patients with comorbidity suggests that while there is evidence that some cancer patients with comorbidity may be at increased risk of post-therapeutic complications; this is not a consistent finding [42–46]. There is increasing evidence that much cancer treatment is tolerated and effective for some people with comorbidities [5, 7–10, 47]. It is likely that the large differences in treatment between those with comorbidity and those without may not always be justifiable from the point of view of treatment toxicity and complications [42]. There are two important implications of the findings of this review in relation to comorbidity. First, given the impact of lack of information on comorbidity both on the ability to make decisions in the MDT context, and for those decisions to be implemented, it seems reasonable to recommend that MDTs should systematically consider the comorbid status of patients. Other authors have made similar recommendations [17, 29, 34]. Second, very careful consideration should be given to the impact of comorbidity on treatment decisions. The inclusion of comorbidity in MDT decision making will only impact positively on care if it does not result in either under or over-treating such patients. This balance is a difficult one to achieve given the paucity of evidence to inform the issue. Given that MDT members tend to overrate their performance, particularly in relation to patient-centred information [15], it is likely that members are not aware of the extent that issues, such as comorbidity, are ignored. From a methodological viewpoint, this review reveals a number of shortcomings in the evidence base about consideration of comorbidity in MDT decision making. The studies were heterogeneous with diverse aims, samples and methodologies creating few opportunities for comparison between studies. The sample sizes in the quantitative studies were relatively small. All of the studies originated from developed countries and were published in English, and none assessed whether explicit consideration of comorbidity in MDTs actually positively impacted patient outcomes. However, these studies demonstrate that MDT decision making can be assessed for consideration of comorbidity using a range of methods including, review of patient records, surveys, meeting observation, semi-structured interviews with MDT participants and ethnography. This review provides a very limited evidence base from which to draw conclusions about consideration of comorbidity in MDTs. However, the literature suggests that comorbidity is rarely considered in MDTs and, when it is, that it may result in more conservative treatment, despite evidence that such treatment may be well tolerated. MDT members are likely to be unaware of the extent to which issues such as comorbidity are ignored. Therefore, MDT members need to be informed of the evidence about the effectiveness of treatment of comorbid patients, standardized information about patient comorbidity should be gathered and provided to MDTs, and members should systematically consider treatment in light of this evidence of effectiveness for comorbid patients. If not, MDTs continue to be at risk of making
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non-evidence-based recommendations that may adversely impact on patient outcomes. Further research is needed to assist clinicians to undertake MDT decision making that appropriately addresses comorbidity. Lamb et al. [15] provide the basis for a toolkit for MDTs to use to evaluate decision making in their meetings. It would be good to see this, and other supports, developed in order to assist MDTs, including to appropriately address comorbidity. If this were to occur, it would likely contribute to improved outcomes for cancer patients with comorbidities.
acknowledgements We thank the other members of the C3 research team who have contributed to our learning in this arena.
funding This work was supported by a grant from the Health Research Council of New Zealand (Grant 11/202).
disclosure The authors have declared no conflicts of interest.
references 1. Extermann M. Measuring comorbidity in older cancer patients. Eur J Cancer 2000; 36(4): 453–471. 2. Piccirillo JF, Tierney RM, Costas I et al. Prognostic importance of comorbidity in a hospital-based cancer registry. JAMA 2004; 291(20): 2441–2447. 3. Read WL, Tierney RM, Page NC et al. Differential prognostic impact of comorbidity. J Clin Oncol 2004; 22: 3099–3103. 4. Stevens W, Stevens G, Kolbe J, Cox B. Ethnic differences in the management of lung cancer in New Zealand. J Thorac Oncol 2008; 3(3): 237–244. 5. Sarfati D, Hill S, Blakely T et al. The effect of comorbidity on the use of adjuvant chemotherapy and survival from colon cancer: a retrospective cohort study. BMC Cancer 2009; 9. doi: 10.1186/1471-2407-1189-1116. 6. Baldwin L-M, Klabunde CN, Green P et al. In search of the perfect comorbidity measure for use with administrative claims data: does it exist? Med Care 2006; 44 (8): 745–753. 7. Velanovich V, Gabel M, Walker EM et al. Causes for the undertreatment of elderly breast cancer patients: tailoring treatments to individual patients. J Am Coll Surg 2002; 194(1): 8–13. 8. Cronin DP, Harlan LC, Potosky AL et al. Patterns of care for adjuvant therapy in a random population-based sample of patients diagnosed with colorectal cancer. Am J Gastroenterol 2006; 101(10): 2308–2318. 9. Gross CP, McAvay GJ, Guo Z, Tinetti ME. The impact of chronic illnesses on the use and effectiveness of adjuvant chemotherapy for colon cancer. Cancer 2007; 109(12): 2410–2419. 10. Etzioni DA, El-Khoueiry AB, Beart RW. Rates and predictors of chemotherapy use for stage III colon cancer. Cancer 2008; 113: 3279–3289. 11. Department of Health. Manual for Cancer Services 2004. London: Department of Health 2004. 12. Taylor C, Munro AJ, Glynne-Jones R et al. Multidisciplinary team working in cancer: what is the evidence? BMJ 2010; 340: c951. 13. Lamb BWM, Brown KFP, Nagpal K et al. Quality of care management decisions by multidisciplinary cancer teams: a systematic review. Ann Surg Oncol 2011; 18(8): 2116–2125. 14. Kidger J, Murdoch J, Donovan JL, Blazeby JM. Clinical decision-making in a multidisciplinary gynaecological cancer team: a qualitative study. BJOG 2009; 116 (4): 511–517.
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reviews 15. Lamb BW, Sevdalis N, Mostafid H et al. Quality improvement in multidisciplinary cancer teams: an investigation of teamwork and clinical decision-making and cross-validation of assessments. Ann Surg Oncol 2011; 18(13): 3535–3543. 16. Arora S, Ashrafian H, Davis R et al. Emotional intelligence in medicine: a systematic review through the context of the ACGME competencies. Med Educ 2010; 44(8): 749–764. 17. Blazeby JM, Wilson L, Metcalfe C et al. Analysis of clinical decision-making in multi-disciplinary cancer teams. Ann Oncol 2006; 17(3): 457–460. 18. Vinod SK, Sidhom MA, Delaney GP. Do multidisciplinary meetings follow guidelinebased care? J Oncol Pract 2010; 6(6): 276–281. 19. Vinod SK, Sidhom MA, Gabriel GS et al. Why do some lung cancer patients receive no anticancer treatment? J Thorac Oncol 2010; 5(7): 1025–1032. 20. Wood JJ, Metcalfe C, Paes A et al. An evaluation of treatment decisions at a colorectal cancer multi-disciplinary team. Colorectal Dis 2008; 10(8): 769–772. 21. English R, Metcalfe C, Day J et al. A prospective analysis of implementation of multi-disciplinary team decisions in breast cancer. Breast J 2012; 18(5): 459–463. 22. Chan WF, Cheung PSY, Epstein RJ, Mak J. Multidisciplinary approach to the management of breast cancer in Hong Kong. World J Surg 2006; 30(12): 2095–2100. 23. Lamb B, Payne H, Vincent C et al. The role of oncologists in multidisciplinary cancer teams in the UK: an untapped resource for team leadership? J Eval Clin Pract 2011; 17(6): 1200–1206. 24. Osarogiagbon RU, Phelps G, McFarlane J, Bankole O. Causes and consequences of deviation from multidisciplinary care in thoracic oncology. J Thorac Oncol 2011; 6(3): 510–516. 25. Stalfors J, Lundberg C, Westin T. Quality assessment of a multidisciplinary tumour meeting for patients with head and neck cancer. Acta Otolaryngol 2007; 127(1): 82–87. 26. Bumm R, Feith M, Lordick F et al. Impact of multidisciplinary tumor boards on diagnosis and treatment of esophageal cancer. Eur Surg Acta Chir Aust 2007; 39 (3): 136–140. 27. Kurtz J-E, Heitz D, Serra S et al. Adjuvant chemotherapy in elderly patients with colorectal cancer. A retrospective analysis of the implementation of tumor board recommendations in a single institution. Crit Rev Oncol Hematol 2010; 74(3): 211–217. 28. Barthélémy P, Heitz D, Mathelin C et al. Adjuvant chemotherapy in elderly patients with early breast cancer. Impact of age and comprehensive geriatric assessment on tumor board proposals. Crit Rev Oncol Hematol 2011; 79(2): 196–204. 29. Kastner C, Armitage J, Kimble A et al. The Charlson comorbidity score: a superior comorbidity assessment tool for the prostate cancer multidisciplinary meeting. Prostate Cancer Prostatic Dis 2006; 9(3): 270–274. 30. Rajan S, Foreman J, Wallis M et al. Multidisciplinary decisions in breast cancer: does the patient receive what the team has recommended? Br J Cancer 2013; 108(12): 2442–2447. 31. Lanceley A, Savage J, Menon U, Jacobs I. Influences on multidisciplinary team decision-making. Int J Gynecol Cancer 2008; 18(2): 215–222. 32. Lamb BW, Sevdalis N, Arora S et al. Teamwork and team decision-making at multidisciplinary cancer conferences: barriers, facilitators, and opportunities for improvement. World J Surg 2011; 35(9): 1970–1976. 33. Devitt B, Philip J, McLachlan S. Team dynamics, decision making, and attitudes toward multidisciplinary cancer meetings: health professionals’ perspectives. J Oncol Pract 2010; 6(6): e17–e20. 34. Jalil R, Ahmed M, Green JSA, Sevdalis N. Factors that can make an impact on decision-making and decision implementation in cancer multidisciplinary teams: an interview study of the provider perspective. Int J Surg 2013; 11(5): 389–394. 35. Sarkar S, Arora S, Lamb BW et al. Case review in urology multidisciplinary team meetings: what members think of its functioning. J Clin Urol 2014; 7: 394–402. 36. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987; 40(5): 373–383. 37. Bellera C, Praud D, Petit-Moneger A et al. Barriers to inclusion of older adults in randomised controlled clinical trials on non-Hodgkin’s lymphoma: a systematic review. Cancer Treat Rev 2013; 39(7): 812–817.
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reviews 38. Fortin M, Dionne J, Pinho G et al. Randomized controlled trials: do they have external validity for patients with multiple comorbidities? Ann Fam Med 2006; 4 (2): 104–108. 39. Keating NL, Landrum MB, Klabunde CN. Adjuvant chemotherapy for stage III colon cancer: do physicians agree about the importance of patient age and comorbidity? J Clin Oncol 2008; 26(15): 2532–2537. 40. Krzyzanowska MK, Regan MM, Powell M et al. Impact of patient age and comorbidity on surgeon versus oncologist preferences for adjuvant chemotherapy for stage III colon cancer. J Am Coll Surg 2009; 208(2): 202–209. 41. Ring A. The influences of age and co-morbidities on treatment decisions for patients with HER2-positive early breast cancer. Crit Rev Oncol Hematol 2010; 76 (2): 127–132. 42. Gronberg BH, Sundstrom S, Kaasa S et al. Influence of comorbidity on survival, toxicity and health-related quality of life in patients with advanced non-small-cell lung cancer receiving platinum-doublet chemotherapy. Eur J Cancer 2010; 46(12): 2225–2234.
| Stairmand et al.
Annals of Oncology 43. Lee L, Cheung WY, Atkinson E, Krzyzanowska MK. Impact of comorbidity on chemotherapy use and outcomes in solid tumors: a systematic review. J Clin Oncol 2011; 29(1): 106–117. 44. Lemmens VEPP, Janssen-Heijnen MLG, Houterman S et al. Which comorbid conditions predict complications after surgery for colorectal cancer? World J Surg 2007; 31(1): 192–199. 45. LoConte NK, Smith M, Alberti D et al. Amongst eligible patients, age and comorbidity do not predict for dose-limiting toxicity from phase I chemotherapy. Cancer Chemother Pharmacol 2010; 65(4): 775–780. 46. Meyerhardt JA, Catalano PJ, Haller DG et al. Impact of diabetes mellitus on outcomes in patients with colon cancer. J Clin Oncol 2003; 21(3): 433–440. 47. Hill S, Sarfati D, Blakely T et al. Survival disparities in Indigenous and nonIndigenous New Zealanders with colon cancer: the role of patient comorbidity, treatment and health service factors. J Epidemiol Commun Health 2010; 64: 117–123.
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Annals of Oncology 26: 1325–1332, 2015 doi:10.1093/annonc/mdv025 Published online 20 January 2015
Consideration of comorbidity in treatment decision making in multidisciplinary cancer team meetings: a systematic review J. Stairmand1, L. Signal1*, D. Sarfati1, C. Jackson2, L. Batten3, M. Holdaway3 & C. Cunningham3 1 Cancer Control and Screening Research Group, University of Otago, Wellington; 2Department of Medicine, University of Otago, Dunedin; 3Research Centre for Ma¯ori Health and Development, Massey University, Palmerston North, New Zealand
Received 20 September 2014; revised 24 November 2014 and 16 December 2014; accepted 17 December 2014
Background: Comorbidity is very common among patients with cancer. Multidisciplinary team meetings (MDTs) are increasingly the context within which cancer treatment decisions are made internationally. Little is known about how comorbidity is considered, or impacts decisions, in MDTs. Methods: A systematic literature review was conducted to evaluate previous evidence on consideration, and impact, of comorbidity in cancer MDT treatment decision making. Twenty-one original studies were included. Results: Lack of information on comorbidity in MDTs impedes the ability of MDT members to make treatment recommendations, and for those recommendations to be implemented among patients with comorbidity. Where treatment is different from that recommended due to comorbidity, it is more conservative, despite evidence that such treatment may be tolerated and effective. MDT members are likely to be unaware of the extent to which issues such as comorbidity are ignored. Conclusions: MDTs should systematically consider treatment of patients with comorbidity. Further research is needed to assist clinicians to undertake MDT decision making that appropriately addresses comorbidity. If this were to occur, it would likely contribute to improved outcomes for cancer patients with comorbidities. Key words: cancer, comorbidity, decision making, multidisciplinary team meetings, systematic review
introduction Comorbidity is very common among patients with cancer and its consequences pose a major clinical challenge in the treatment of cancer. As comorbidities may adversely affect an individual’s access to, and the effectiveness of, major cancer treatments, it is also a significant prognostic factor for long-term survival from cancer [1–3]. Comorbidity acts on survival both through direct mechanisms related to the increased physiological burden of disease, and through indirect mechanisms related to the effects comorbidity has on treatment choice, timeliness and/or effectiveness. Cancer patients with comorbidity are considerably less likely to be offered active therapy [4–6]. However, there is growing evidence that such treatments can be both tolerated and effective by some patients with comorbidity [5, 7–10]. Internationally, multidisciplinary team meetings (MDTs) are increasingly the context within which cancer treatment decisions are made. In the literature, MDTs are referred to using a number of terms e.g. tumour boards, tumour meetings and multidisciplinary cancer team meetings. In this paper, we use the
*Correspondence to: Dr. Louise Signal, Cancer Control and Screening Research Group, University of Otago, PO Box 7343, Wellington South, Wellington 6242, New Zealand. Tel: +64-4-385-5541; Fax: +64-4-389-5319; E-mail: [email protected]
term MDT for consistency to refer to a ‘group of people of different healthcare disciplines, which meets together at a given time (whether physically in one place, or by video or teleconferencing) to discuss a given patient and who are each able to contribute independently to the diagnostic and treatment decisions about the patient’ [11]. MDTs are often highly pressurized, with high caseloads, little time to process highly technical information, and frequently have members absent [12–14]. Nevertheless, there is growing evidence that MDTs are associated with ‘improved clinical decision making, clinical outcomes, patient experience, and the working lives of team members’ [12]. Efforts are being made to find ways to strengthen MDT functioning [15]. Little is known about how comorbidity impacts decisions in cancer MDTs. The aim of this systematic review is to summarize and evaluate previous evidence on consideration, and impact, of comorbidity in cancer MDT treatment decision making and to make suggestions for future practice and research.
materials and methods Studies that reported the findings of original research which met the following criteria were included in this review: (i) published from January 2005 to May 2014 and in English in peer-reviewed journals, (ii) investigated MDT treatment decision making as a
© The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: [email protected].
reviews primary or secondary objective, (iii) the MDT was focused on addressing a certain type, or types, of cancer, (iv) the studies addressed comorbidity. The studies were identified using a systematic search of electronic databases, including Medline, CINAHL, Cochrane CENTRAL and Embase. The reference lists of retrieved articles included in the review were hand-searched and advice sought from experts in the field. Broad search terms were used to ensure all relevant articles were identified. The databases were searched with combinations of terms and variations of the following: ‘decision making’, ‘multidisciplinary team’, ‘neoplasm’ and ‘comorbidity’ (full details of the search strategy can be found in supplementary S1, available at Annals of Oncology online). The studies included were categorized and evaluated by three authors (JS, DS and LS). Methodological evaluation was based on previously established criteria [16]. Findings were synthesized using narrative summary.
results A total of 659 articles were retrieved. Application of the inclusion criteria excluded 638 articles. Excluded articles did not consider comorbidity (see Figure 1 and supplementary S1, available at Annals of Oncology online, for details). The 21 articles reviewed were published between 2006 and 2014. The outcomes in the articles assessed were heterogeneous; thus, a meta-analytic approach was not possible. Of the 21 studies, 15 were quantitative [15, 17–30], and 6 were qualitative [14, 31–35]. Key characteristics of the papers are presented in Table 1. The data sources were information obtained from medical records (n = 13) [17–22, 24–30], surveys (n = 2) [15, 23], routine data (n = 1) [24], observation (n = 2) [14, 15], semi-structured interviews (n = 5) [14, 31, 32, 34, 35], focus group [33] and ethnography [31]. Papers were from UK (n = 12) [14, 15, 17, 20, 21,
• 659 Titles from search Search
• 659 Titles reviewed against inclusion criteria • 72 Titles excluded Titles
Abstracts
Full text articles
Articles for analysis
• 587 Abstracts reviewed • 494 Abstracts excluded
• 93 Full text articles reviewed • 72 Full text articles excluded
• 21 Full text articles included
Figure 1. Article inclusion flow diagram.
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23, 29–32, 34, 35], Australia (n = 3) [18, 19, 33], China [22], USA [24], Germany [26], France (n = 2) [27, 28] and Sweden [25]. Eleven MDT areas of specialty were represented in the original articles: gastrointestinal (n = 2) [17, 34], colorectal (n = 2) [20, 27], lung (n = 2) [18, 19], gynaecology (n = 2) [14, 31], breast (n = 4) [21, 22, 28, 30], head and neck [25], oesophageal [26], thoracic [24], prostate [29], urology (n = 2) [34, 35] and four unspecified [15, 23, 32, 33]. The MDT care studied was centred across UK cancer networks and hospitals (n = 10) [15, 17, 20, 21, 29–32, 34, 35], an Australian cancer therapy centre (n = 2) [18, 19] and hospital [33], hospitals in Hong Kong [22], France (n = 2) [27, 28], Sweden [25], Germany [26] and a Cancer Institute in Tennessee [24]. Fourteen studies looked at patient cases where MDT decisions had been made [15, 17–22, 24–30] and eight involved participants in MDTs [14, 15, 23, 31–35]. A summary of the findings is presented below for each of the thematic areas of interest.
is comorbidity considered in MDTs? There were a number of studies that noted that comorbidity was not well considered in MDTs [14, 15, 23, 29, 32, 34, 35]. Kidger et al. [14] undertook observations of MDTs and interviews with MDT team members in the UK. They found that comorbidity was not routinely presented or discussed unless an MDT participant identified it as having the potential to influence treatment decisions, or when a patient was in particularly poor health. MDT participants had varying opinions about the presentation of comorbidity with some suggesting that it was included as necessary while others thought it needed more attention and could be systematically included [14]. Two other recent studies involving interviews with MDT members found that participants reported that insufficient information on comorbidity was a barrier to decision making [34, 35]. In the UK, Lamb et al. [15] observed MDT meetings and MDT members completed a self-assessment survey. The authors found that comorbidities were not well covered and that team members tended to overrate aspects of their performance, including their consideration of comorbidities. Two other studies noted that comorbidity was not always considered appropriately in MDTs [23, 32]. Kastner et al. [29] aimed to determine whether a particular measure of comorbidity (the Charlson Comorbidity Index) [36] would be a useful addition in the context of a prostate cancer MDT. Based on their finding that, a patient Charlson Comorbidity Index was associated with survival, they concluded that they should adopt this approach to explicitly considering comorbidity in their MDT.
impact of comorbidity on MDT decisions There is evidence in the literature that information on comorbidity (or lack of it) has three implications for MDT decision making. First, MDT decisions are less likely to be made for patients with comorbidity. Three studies [25, 32, 33] found that lack of information on comorbidity was a barrier to reaching a clear treatment plan. Similarly, Kidger et al. [14] noted that, when treatment decisions were not made, this was due to the complexity of the case and the extent of agreement among team members. Clearly, comorbidity could be a reason for such complexity.
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Study question
Main outcome
Sample
Design
Data collection
Barthélémy et al. [28]
France
Elderly patients were less likely to receive adjuvant chemotherapy even when deemed appropriate by guidelines (P < 0.001).
n = 192 decisions
Quantitative
Medical records
Blazeby et al. [17]
UK
What is the impact of age, geriatric assessment and other variables on recommendations by tumour boards for adjuvant chemotherapy in elderly breast cancer patients? Are upper GI MDT decisions implemented?
n = 271 decisions
Quantitative
Medical records
Bumm et al. [26]
Germany
What is the feasibility of a daily tumour MDT in a high-volume university hospital?
OC n = 1238 patients GC n = 1212 patients
Quantitative
Medical records
Chan et al. [22]
China
n = 563 patients
Quantitative
Medical records
Devitt et al. [33]
Australia
What is the applicability of the multidisciplinary approach to the management of breast cancer? What are the views of health professionals attending MDTs of decision making processes and meeting dynamics?
n = 4 focus groups n = 23 participants
Qualitative
Focus group
English et al. [21]
UK
Are breast cancer MDT decisions implemented and what factors influence these processes?
n = 289 decisions n = 210 women
Quantitative
Medical records
Jalil et al. [34]
UK
What are the factors influencing decision making and decision implementation in cancer MDTs?
n = 22 team members
Qualitative
Semi-structured interviews
Kastner et al. [29]
UK
What is the feasibility of using the Charlson Comorbidity Index (CCI) in MDT planning of the treatment of patients with prostate cancer?
15.1% (95% CI 11.1% to 20%) of MDT decisions were not implemented. Reasons for discordance included comorbidity (43.9%). Nonimplementation often resulted in more conservative treatment than originally planned. Comorbidities such as obesity (using BMI) for patients with oesophageal carcinoma (OC) and stress for patients with OC and gastric cancer (GC) are considered by the MDT when evaluating patients’ perioperative risk. Adjuvant treatment was not recommended by the multidisciplinary conference panel for 29 patients owing to old age or concomitant medical illness. Psychosocial concerns of patients were often neglected and at times inadequate information on patients’ comorbid conditions constrained treatment recommendations. 6.9% (95% CI 4.3% to 10.5%) of MDT decisions were not implemented. Reasons for changes to MDT decision were patient preferences (65%), new clinical information (15%) and doctor’s view (20%). Barriers to clinical decision making included: inadequate clinical information; lack of investigation results; non-attendance of key members; teleconferencing failures. Barriers to implementation of MDT recommendations included: non-consideration of patients’ choices or comorbidities; disease progression at the time of implementation. The CCI was a statistically significant predictor of survival, following radical treatment of localized prostate cancer (P = 0.005). The CCI was easy to calculate and therefore feasible to use in the MDT setting.
n = 37 decisions
Quantitative
Medical records
Continued
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Table 1. Characteristics of papers included Study
Country
Study question
Main outcome
Sample
Design
Data collection
Kidger et al. [14]
UK
What factors influence treatment decision making in a gynaecological cancer MDT?
n = 1 MDT n = 16 team members
Qualitative
Meeting observation and semi-structured interviews
Kurtz et al. [27]
France
Does age negatively impact on adjuvant chemotherapy in colorectal MDT decisions?
n = 193 decisions
Quantitative
Medical records
Lamb et al. [32]
UK
What are the attitudes of MDT members; what are the barriers and facilitators for effective teamwork; and what do MDT members consider best practice?
n = 19 MDT members
Qualitative
Semi-structured interviews
Lamb et al. [23]
UK
n = 61 responses
Quantitative
Survey
Lamb et al. [15]
UK
What contribution do oncologists make to MDTs; what is their experience of leadership in MDTs and are they potential MDT leaders? What quality of information is presented by MDT members and who contributes to decision making? Is there correlation between observational and self-reported metrics?
n = 164 cases n = 47 surveys n = 5 MDTs n = 67 team members
Quantitative
Observational tools and on-line selfassessment survey
Lanceley et al. [31]
UK
Patient-centred factors, such as comorbidity, were more peripheral and not routinely discussed. This was partly due to members’ type and level of participation: senior clinicians occupied the most dominant roles whereas nurses contributed less. Disease stage was the major variable leading to adjuvant treatment recommendation, age and comorbidities were of lesser importance. Elderly colorectal cancer patients were not undertreated. Ten respondents agreed that comorbidities (psychological and social problems) were adequately presented. Lack of information on comorbidities was identified by three respondents as a barrier to reaching a clear treatment plan at MDTs. 92% of respondents felt their MDT venue was fit for purpose. Information about patient comorbidities were less likely to be presented in MDTs when their venue was not fit for purpose (P < 0.05, χ 2). Quality of information presented: patient views and comorbidities/psychosocial issues rated lowest. A pronounced difference between expert observer rating and MDT member self-rating was found for the quality of patient-centred information (comorbidities, psychosocial issues, and patients’ views) presented to the team. Contribution to decision making: surgeons and oncologists rated highest and nurses and MDT coordinators lowest. There are three major influences: discussions are dominated by those with medical, surgical or diagnostic expertise; compliance with policy initiatives concerning diagnosis and treatment; and if the patient is known or not by members of the MDT. It was difficult for non-medical team members to contribute to the meeting even when patients had differing characteristics e.g. physical comorbidity.
n = 53 MDT participants
Qualitative
Ethnography, ethnographic field notes, semistructured interviews
What influences clinical decisions made in a gynaecological cancer MDT?
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Study
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Table 1. Continued
What is the benefit of multidisciplinary thoracic oncology MDTs? When care deviates from that recommended what is the impact on patient outcomes? To evaluate the implementation of MDT decisions for patients with breast cancer in a modern breast unit.
Rajan et al. [30]
UK
Sarkar et al. [35]
UK
To explore current practices in urology MDT meeting organization, case preparation and the potential for case selection from the perspective of team members.
Stalfors et al. [25]
Sweden
What is the quality and efficacy of the head and neck oncology MDT?
Vinod et al. [18]
Australia
Are MDT recommendations concordant with guidelines in the treatment of lung cancer?
Vinod et al. [19]
Australia
What are the reasons for lung cancer patients receiving no treatment?
Wood et al. [20]
UK
Are colorectal MDT decisions implemented? And if not why?
235 patients received concordant care and 141 did not. Comorbidity in 14 of 104 instances was identified as a reason for clinician-induced discordance of care. The vast majority of MDT decisions are implemented. Management alteration was most often due to patient choice or additional information available including that related to comorbidity after the MDT. A minority of management alterations were ‘unjustifiable’. Factors negatively influencing the MDTs included insufficient time to prepare cases so that enough information is available to make appropriate decisions: absence of the clinician in charge or not knowing the patient; and lack of a systematic approach to case discussion. Participants recommended improvements including protected time for case preparation and focusing on patient comorbidities. Uncertainty regarding general cardiovascular status (6%) resulted in the inability to establish a diagnosis and treatment plans. 16% of these failures required complementary information. Concordance with guidelines existed in 58% of surgical cases, 88% of radiotherapy cases and 77% of chemotherapy cases. Reasons for MDT not recommending guideline treatment included comorbidity (25%). Guidelines recommended no treatment in 4% of cases compared with 10% by MDT. Differences were due to comorbidities and clinician decision. 20% of patients actually received no treatment. The majority of decisions were implemented. 10% (95% CI 6.3–15.2) were not. Reasons for nonimplementation included comorbidity (40%) resulting in more conservative treatment than planned.
n = 376 patients n = 454 recommendations
Quantitative
Medical records and Social Security Death Index
n = 705 patients n = 3230 MDT decisions
Quantitative
Medical records
n = 20 MDT participants
Qualitative
Semi-structured interviews
n = 324 patients
Quantitative
Medical records
n = 335 patients
Quantitative
Medical records
n = 335 patients
Quantitative
Medical records
n = 201 treatment decisions n = 157 patients
Quantitative
Medical records
reviews
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Osarogiagbon et al. [24]
reviews Second, decisions made for patients with comorbidity are less likely to be concordant with clinical guidelines. Vinod et al. [18, 19] found that 29% of lung cancer patients reviewed in MDTs received care outside of that recommended in the guidelines, and comorbidity was given as the reason for the disparity in a quarter of these [18]. Further, although the guideline recommended no treatment in 4% of patients, MDTs recommended no treatment in 10% [19]. Again, a key reason for the discrepancy was comorbidity (47%). Patients with at least one comorbid condition were more likely to have no treatment (24%) than those who did not have any such conditions (12%) (P = 0.005) [19]. Consistent with these findings, Kurtz et al. [27] assessed the extent to which treatment recommendations from MDTs within a single institute were consistent with guidelines. They found that both comorbidity and ‘old age’ were frequently cited causes for discordant treatment. Similarly, Chan et al. [22] found that comorbidity was cited as a reason for not recommending adjuvant treatment. In contrast, Barthélémy et al. [28] assessed whether recommendations for adjuvant chemotherapy for elderly patients with breast cancer were associated with categorization according to the Comprehensive Geriatric Assessment (which includes an assessment of comorbidity) and found little association. However, when patients did not receive recommended chemotherapy, age and comorbidity were still often cited as reasons. Third, that even when treatment decisions are reached in MDTs, the actual treatment received is more likely to be discordant with that decision among patients with comorbidity. Several studies investigated reasons why MDT decisions were not implemented [17, 20–22, 24, 27, 28, 30, 34]. All but one [21] found comorbidity was an important reason for this discordance. Of the eight studies that found comorbidity was a reason for not implementing decisions [17, 20, 22, 24, 27, 28, 30, 34], seven were reviews of medical records [17, 20, 22, 24, 27, 28, 30] and one a report of MDT participants’ perspectives [34]. When decisions were changed post-MDT, as a result of new information about comorbidity, they resulted in more conservative treatment [17, 20].
discussion To the best of our knowledge, this is the first review to assess consideration of comorbidity, and its impact, in cancer MDT decision making. We found a limited number of articles which examined comorbidity. The review results suggest that comorbidity is not well considered in MDTs [14, 15, 23, 29, 32, 34, 35]. MDTs are less likely to make treatment recommendations for patients with comorbidity [14, 25, 33] and, when recommendations are made, comorbidity appears to be a key reason for MDTs not making these in line with guidelines [18, 19, 22, 27, 28]. Further, when recommendations are made, comorbidity is a key reason for not implementing these [17, 20, 22, 24, 27, 28, 30, 34]. The evidence relating to the potential benefits and harms of cancer treatments among patients with comorbidity is scarce, not least of all because patients with comorbidity are often excluded from relevant randomized controlled trials [37, 38]. Consistent with the findings of this review, a number of vignette-based studies have found that surgeons and oncologists
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are less likely to refer or recommend treatment of cancer patients with comorbidity [39–41]. Clinicians may be concerned about potential toxicity or effectiveness of treatments among those with comorbidity, and/or may consider that some patients’ life expectancy is too short to justify the risks of treatment. In fact, research relating to the risk of complications and effectiveness of cancer treatment in patients with comorbidity suggests that while there is evidence that some cancer patients with comorbidity may be at increased risk of post-therapeutic complications; this is not a consistent finding [42–46]. There is increasing evidence that much cancer treatment is tolerated and effective for some people with comorbidities [5, 7–10, 47]. It is likely that the large differences in treatment between those with comorbidity and those without may not always be justifiable from the point of view of treatment toxicity and complications [42]. There are two important implications of the findings of this review in relation to comorbidity. First, given the impact of lack of information on comorbidity both on the ability to make decisions in the MDT context, and for those decisions to be implemented, it seems reasonable to recommend that MDTs should systematically consider the comorbid status of patients. Other authors have made similar recommendations [17, 29, 34]. Second, very careful consideration should be given to the impact of comorbidity on treatment decisions. The inclusion of comorbidity in MDT decision making will only impact positively on care if it does not result in either under or over-treating such patients. This balance is a difficult one to achieve given the paucity of evidence to inform the issue. Given that MDT members tend to overrate their performance, particularly in relation to patient-centred information [15], it is likely that members are not aware of the extent that issues, such as comorbidity, are ignored. From a methodological viewpoint, this review reveals a number of shortcomings in the evidence base about consideration of comorbidity in MDT decision making. The studies were heterogeneous with diverse aims, samples and methodologies creating few opportunities for comparison between studies. The sample sizes in the quantitative studies were relatively small. All of the studies originated from developed countries and were published in English, and none assessed whether explicit consideration of comorbidity in MDTs actually positively impacted patient outcomes. However, these studies demonstrate that MDT decision making can be assessed for consideration of comorbidity using a range of methods including, review of patient records, surveys, meeting observation, semi-structured interviews with MDT participants and ethnography. This review provides a very limited evidence base from which to draw conclusions about consideration of comorbidity in MDTs. However, the literature suggests that comorbidity is rarely considered in MDTs and, when it is, that it may result in more conservative treatment, despite evidence that such treatment may be well tolerated. MDT members are likely to be unaware of the extent to which issues such as comorbidity are ignored. Therefore, MDT members need to be informed of the evidence about the effectiveness of treatment of comorbid patients, standardized information about patient comorbidity should be gathered and provided to MDTs, and members should systematically consider treatment in light of this evidence of effectiveness for comorbid patients. If not, MDTs continue to be at risk of making
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non-evidence-based recommendations that may adversely impact on patient outcomes. Further research is needed to assist clinicians to undertake MDT decision making that appropriately addresses comorbidity. Lamb et al. [15] provide the basis for a toolkit for MDTs to use to evaluate decision making in their meetings. It would be good to see this, and other supports, developed in order to assist MDTs, including to appropriately address comorbidity. If this were to occur, it would likely contribute to improved outcomes for cancer patients with comorbidities.
acknowledgements We thank the other members of the C3 research team who have contributed to our learning in this arena.
funding This work was supported by a grant from the Health Research Council of New Zealand (Grant 11/202).
disclosure The authors have declared no conflicts of interest.
references 1. Extermann M. Measuring comorbidity in older cancer patients. Eur J Cancer 2000; 36(4): 453–471. 2. Piccirillo JF, Tierney RM, Costas I et al. Prognostic importance of comorbidity in a hospital-based cancer registry. JAMA 2004; 291(20): 2441–2447. 3. Read WL, Tierney RM, Page NC et al. Differential prognostic impact of comorbidity. J Clin Oncol 2004; 22: 3099–3103. 4. Stevens W, Stevens G, Kolbe J, Cox B. Ethnic differences in the management of lung cancer in New Zealand. J Thorac Oncol 2008; 3(3): 237–244. 5. Sarfati D, Hill S, Blakely T et al. The effect of comorbidity on the use of adjuvant chemotherapy and survival from colon cancer: a retrospective cohort study. BMC Cancer 2009; 9. doi: 10.1186/1471-2407-1189-1116. 6. Baldwin L-M, Klabunde CN, Green P et al. In search of the perfect comorbidity measure for use with administrative claims data: does it exist? Med Care 2006; 44 (8): 745–753. 7. Velanovich V, Gabel M, Walker EM et al. Causes for the undertreatment of elderly breast cancer patients: tailoring treatments to individual patients. J Am Coll Surg 2002; 194(1): 8–13. 8. Cronin DP, Harlan LC, Potosky AL et al. Patterns of care for adjuvant therapy in a random population-based sample of patients diagnosed with colorectal cancer. Am J Gastroenterol 2006; 101(10): 2308–2318. 9. Gross CP, McAvay GJ, Guo Z, Tinetti ME. The impact of chronic illnesses on the use and effectiveness of adjuvant chemotherapy for colon cancer. Cancer 2007; 109(12): 2410–2419. 10. Etzioni DA, El-Khoueiry AB, Beart RW. Rates and predictors of chemotherapy use for stage III colon cancer. Cancer 2008; 113: 3279–3289. 11. Department of Health. Manual for Cancer Services 2004. London: Department of Health 2004. 12. Taylor C, Munro AJ, Glynne-Jones R et al. Multidisciplinary team working in cancer: what is the evidence? BMJ 2010; 340: c951. 13. Lamb BWM, Brown KFP, Nagpal K et al. Quality of care management decisions by multidisciplinary cancer teams: a systematic review. Ann Surg Oncol 2011; 18(8): 2116–2125. 14. Kidger J, Murdoch J, Donovan JL, Blazeby JM. Clinical decision-making in a multidisciplinary gynaecological cancer team: a qualitative study. BJOG 2009; 116 (4): 511–517.
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reviews 15. Lamb BW, Sevdalis N, Mostafid H et al. Quality improvement in multidisciplinary cancer teams: an investigation of teamwork and clinical decision-making and cross-validation of assessments. Ann Surg Oncol 2011; 18(13): 3535–3543. 16. Arora S, Ashrafian H, Davis R et al. Emotional intelligence in medicine: a systematic review through the context of the ACGME competencies. Med Educ 2010; 44(8): 749–764. 17. Blazeby JM, Wilson L, Metcalfe C et al. Analysis of clinical decision-making in multi-disciplinary cancer teams. Ann Oncol 2006; 17(3): 457–460. 18. Vinod SK, Sidhom MA, Delaney GP. Do multidisciplinary meetings follow guidelinebased care? J Oncol Pract 2010; 6(6): 276–281. 19. Vinod SK, Sidhom MA, Gabriel GS et al. Why do some lung cancer patients receive no anticancer treatment? J Thorac Oncol 2010; 5(7): 1025–1032. 20. Wood JJ, Metcalfe C, Paes A et al. An evaluation of treatment decisions at a colorectal cancer multi-disciplinary team. Colorectal Dis 2008; 10(8): 769–772. 21. English R, Metcalfe C, Day J et al. A prospective analysis of implementation of multi-disciplinary team decisions in breast cancer. Breast J 2012; 18(5): 459–463. 22. Chan WF, Cheung PSY, Epstein RJ, Mak J. Multidisciplinary approach to the management of breast cancer in Hong Kong. World J Surg 2006; 30(12): 2095–2100. 23. Lamb B, Payne H, Vincent C et al. The role of oncologists in multidisciplinary cancer teams in the UK: an untapped resource for team leadership? J Eval Clin Pract 2011; 17(6): 1200–1206. 24. Osarogiagbon RU, Phelps G, McFarlane J, Bankole O. Causes and consequences of deviation from multidisciplinary care in thoracic oncology. J Thorac Oncol 2011; 6(3): 510–516. 25. Stalfors J, Lundberg C, Westin T. Quality assessment of a multidisciplinary tumour meeting for patients with head and neck cancer. Acta Otolaryngol 2007; 127(1): 82–87. 26. Bumm R, Feith M, Lordick F et al. Impact of multidisciplinary tumor boards on diagnosis and treatment of esophageal cancer. Eur Surg Acta Chir Aust 2007; 39 (3): 136–140. 27. Kurtz J-E, Heitz D, Serra S et al. Adjuvant chemotherapy in elderly patients with colorectal cancer. A retrospective analysis of the implementation of tumor board recommendations in a single institution. Crit Rev Oncol Hematol 2010; 74(3): 211–217. 28. Barthélémy P, Heitz D, Mathelin C et al. Adjuvant chemotherapy in elderly patients with early breast cancer. Impact of age and comprehensive geriatric assessment on tumor board proposals. Crit Rev Oncol Hematol 2011; 79(2): 196–204. 29. Kastner C, Armitage J, Kimble A et al. The Charlson comorbidity score: a superior comorbidity assessment tool for the prostate cancer multidisciplinary meeting. Prostate Cancer Prostatic Dis 2006; 9(3): 270–274. 30. Rajan S, Foreman J, Wallis M et al. Multidisciplinary decisions in breast cancer: does the patient receive what the team has recommended? Br J Cancer 2013; 108(12): 2442–2447. 31. Lanceley A, Savage J, Menon U, Jacobs I. Influences on multidisciplinary team decision-making. Int J Gynecol Cancer 2008; 18(2): 215–222. 32. Lamb BW, Sevdalis N, Arora S et al. Teamwork and team decision-making at multidisciplinary cancer conferences: barriers, facilitators, and opportunities for improvement. World J Surg 2011; 35(9): 1970–1976. 33. Devitt B, Philip J, McLachlan S. Team dynamics, decision making, and attitudes toward multidisciplinary cancer meetings: health professionals’ perspectives. J Oncol Pract 2010; 6(6): e17–e20. 34. Jalil R, Ahmed M, Green JSA, Sevdalis N. Factors that can make an impact on decision-making and decision implementation in cancer multidisciplinary teams: an interview study of the provider perspective. Int J Surg 2013; 11(5): 389–394. 35. Sarkar S, Arora S, Lamb BW et al. Case review in urology multidisciplinary team meetings: what members think of its functioning. J Clin Urol 2014; 7: 394–402. 36. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987; 40(5): 373–383. 37. Bellera C, Praud D, Petit-Moneger A et al. Barriers to inclusion of older adults in randomised controlled clinical trials on non-Hodgkin’s lymphoma: a systematic review. Cancer Treat Rev 2013; 39(7): 812–817.
doi:10.1093/annonc/mdv025 |
reviews 38. Fortin M, Dionne J, Pinho G et al. Randomized controlled trials: do they have external validity for patients with multiple comorbidities? Ann Fam Med 2006; 4 (2): 104–108. 39. Keating NL, Landrum MB, Klabunde CN. Adjuvant chemotherapy for stage III colon cancer: do physicians agree about the importance of patient age and comorbidity? J Clin Oncol 2008; 26(15): 2532–2537. 40. Krzyzanowska MK, Regan MM, Powell M et al. Impact of patient age and comorbidity on surgeon versus oncologist preferences for adjuvant chemotherapy for stage III colon cancer. J Am Coll Surg 2009; 208(2): 202–209. 41. Ring A. The influences of age and co-morbidities on treatment decisions for patients with HER2-positive early breast cancer. Crit Rev Oncol Hematol 2010; 76 (2): 127–132. 42. Gronberg BH, Sundstrom S, Kaasa S et al. Influence of comorbidity on survival, toxicity and health-related quality of life in patients with advanced non-small-cell lung cancer receiving platinum-doublet chemotherapy. Eur J Cancer 2010; 46(12): 2225–2234.
| Stairmand et al.
Annals of Oncology 43. Lee L, Cheung WY, Atkinson E, Krzyzanowska MK. Impact of comorbidity on chemotherapy use and outcomes in solid tumors: a systematic review. J Clin Oncol 2011; 29(1): 106–117. 44. Lemmens VEPP, Janssen-Heijnen MLG, Houterman S et al. Which comorbid conditions predict complications after surgery for colorectal cancer? World J Surg 2007; 31(1): 192–199. 45. LoConte NK, Smith M, Alberti D et al. Amongst eligible patients, age and comorbidity do not predict for dose-limiting toxicity from phase I chemotherapy. Cancer Chemother Pharmacol 2010; 65(4): 775–780. 46. Meyerhardt JA, Catalano PJ, Haller DG et al. Impact of diabetes mellitus on outcomes in patients with colon cancer. J Clin Oncol 2003; 21(3): 433–440. 47. Hill S, Sarfati D, Blakely T et al. Survival disparities in Indigenous and nonIndigenous New Zealanders with colon cancer: the role of patient comorbidity, treatment and health service factors. J Epidemiol Commun Health 2010; 64: 117–123.
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