PORTRET, a more inclusive portrait of the older population with breast cancer
Authors: Etienne G C Brain
Journal: The Lancet Healthy Longevity (2021)

At a time when virtual life and digitalised techniques have invaded our everyday life, creating the illusion that they can replace reality, it is heartening to read the outcome of the work by Willeke van der Plas-Krijgsman and colleagues in The Lancet Healthy Longevity.1van der Plas-Krijgsman WG Giardiello D Putter H et al.Development and validation of the PORTRET tool to predict recurrence, overall survival, and other-cause mortality in older patients with breast cancer in the Netherlands: a population-based study.Lancet Healthy Longev. 2021; 2: e704-e711Summary Full Text Full Text PDF Scopus (3) Google ScholarFocusing on the growing ageing population of patients with breast cancer, the authors attempted to improve the methods that exist to accurately estimate the global prognosis of patients aged 65 years and older, who represent nearly 50% of new cases of breast cancer in so many countries.2Pilleron S Soto-Perez-de-Celis E Vignat J et al.Estimated global cancer incidence in the oldest adults in 2018 and projections to 2050.Int J Cancer. 2021; 148: 601-608Crossref PubMed Scopus (78) Google Scholar They also attempted to further help guiding the challenging decision for adjuvant treatment.3Biganzoli L Battisti NML Wildiers H et al.Updated recommendations regarding the management of older patients with breast cancer: a joint paper from the European Society of Breast Cancer Specialists (EUSOMA) and the International Society of Geriatric Oncology (SIOG).Lancet Oncol. 2021; 22: e327-e340Summary Full Text Full Text PDF PubMed Scopus (41) Google ScholarOne should congratulate them for this effort. Indeed, most scientific efforts seem to be diverted towards digging deeper in the understanding of the biology of cancer, leading to ambitious and costly gene expression profiling, but ironically leaving behind the majority of those with cancer, namely the older population, and the hot topic of competing risks.3Biganzoli L Battisti NML Wildiers H et al.Updated recommendations regarding the management of older patients with breast cancer: a joint paper from the European Society of Breast Cancer Specialists (EUSOMA) and the International Society of Geriatric Oncology (SIOG).Lancet Oncol. 2021; 22: e327-e340Summary Full Text Full Text PDF PubMed Scopus (41) Google Scholar, 4Kendal WS Dying with cancer: the influence of age, comorbidity, and cancer site.Cancer. 2008; 112: 1354-1362Crossref PubMed Scopus (71) Google Scholar Comorbidities increase with age, in both incidence or severity,5Piccirillo JF Vlahiotis A Barrett LB Flood KL Spitznagel EL Steyerberg EW The changing prevalence of comorbidity across the age spectrum.Crit Rev Oncol Hematol. 2008; 67: 124-132Crossref PubMed Scopus (201) Google Scholar making patients’ overall outcomes difficult to determine.4Kendal WS Dying with cancer: the influence of age, comorbidity, and cancer site.Cancer. 2008; 112: 1354-1362Crossref PubMed Scopus (71) Google Scholar Good medical practice cannot solely consider tumour biology and omit wider considerations as comorbidities.The UK National Health Service (NHS) developed the PREDICT algorithm, which became hitherto the most successful and validated algorithm to predict outcomes at 5 years for older patients, although no geriatric data for comorbidities were included.6de Glas NA Bastiaannet E Engels CC et al.Validity of the online PREDICT tool in older patients with breast cancer: a population-based study.Br J Cancer. 2016; 114: 395-400Crossref PubMed Scopus (48) Google Scholar Of note, the validity of the model could not be proven for prediction at 10 years, and there were limitations for patients aged 80 years or older stressing the impact of age on the meaningful value of temporality.Therefore, van der Plas-Krijgsman and colleagues created a refined prognostic tool using data from the FOCUS cohort, to predict 5-year recurrence, overall mortality, and other-cause mortality in patients aged 65 years and older with early-stage breast cancer. For external validation, they used a national cancer registry that was five times the size of the development set. While based on simple and very pragmatic inexpensive items covering both the disease and the host, the final PORTRET model is robust and could accurately predict the three outcome endpoints of interest in these older patients. Moreover, it seems to outperform PREDICT. These findings highlight the crucial need to factor in variables beyond the disease itself, with a capture of the geriatric health status, as it was done in the full model, which included comorbidities, functional status, polypharmacy, cognitive defects, and sensory deficiency.Whether one should consider the prediction advantage provided by PORTRET as small or significant seems immaterial. By including specific geriatric data, PORTRET was able to better discriminate than the submodel (similar to PREDICT) or the reduced model that were tested by the Dutch investigators. This finding demonstrates, first, the importance of considering other variables than the ones commonly assessed in oncology to potentially fine-tune adjuvant treatment in older patients. Second, it demonstrates that, although overall survival used in PORTRET might be too global, this outcome might still better reflect a certain quality of life or maintenance of dependence (both highly sought by the older persons) than the breast-cancer specific outcomes that are usually preferred in oncology programmes.One should stress that not a single large study of gene-expression assay validation enrolled a relevant number of older patients, if any at all. There is a growing trend to use this lack of inclusion of older patients in clinical trials to justify relegating research in this population to non-controlled data from registries or insurance programmes. This approach should be considered as a form of ageism, especially given the usual selection biases of real world data. This leads to poorer management, for example, whereby supposedly age-agnostic prognostic signatures for tailored treatments developed from such datasets lead to beneficial outcomes only for younger patients.7Kizy S Altman AM Marmor S et al.21-gene recurrence score testing in the older population with estrogen receptor-positive breast cancer.J Geriatr Oncol. 2019; 10: 322-329Summary Full Text Full Text PDF PubMed Scopus (22) Google ScholarFinally, this work appears as a culmination of previous landmark publications by the same group, highlighting the perseverance required to change mindsets through gradual demonstration, and reminding what should be a leitmotiv rule in research: evidence-based information for a relevant population.As long as the best information obtained from the tumour biology and from the patient is not reconciled in joined models, research in geriatric oncology will remain essentially partial and slightly opportunistic, not comprehensively supported by an oncology world often disconnected from reality, with very little chance to bring important and relevant changes in attitudes. Such PORTRET data should be tested with modern molecular portraits to reach a more mixed and inclusive model closer to reality. It is only this way that the fast-moving field of biology in oncology will find a realistic application to the older population, a segment of patients far from being virtual and with a clear unmet medical need. At a time when virtual life and digitalised techniques have invaded our everyday life, creating the illusion that they can replace reality, it is heartening to read the outcome of the work by Willeke van der Plas-Krijgsman and colleagues in The Lancet Healthy Longevity.1van der Plas-Krijgsman WG Giardiello D Putter H et al.Development and validation of the PORTRET tool to predict recurrence, overall survival, and other-cause mortality in older patients with breast cancer in the Netherlands: a population-based study.Lancet Healthy Longev. 2021; 2: e704-e711Summary Full Text Full Text PDF Scopus (3) Google Scholar Focusing on the growing ageing population of patients with breast cancer, the authors attempted to improve the methods that exist to accurately estimate the global prognosis of patients aged 65 years and older, who represent nearly 50% of new cases of breast cancer in so many countries.2Pilleron S Soto-Perez-de-Celis E Vignat J et al.Estimated global cancer incidence in the oldest adults in 2018 and projections to 2050.Int J Cancer. 2021; 148: 601-608Crossref PubMed Scopus (78) Google Scholar They also attempted to further help guiding the challenging decision for adjuvant treatment.3Biganzoli L Battisti NML Wildiers H et al.Updated recommendations regarding the management of older patients with breast cancer: a joint paper from the European Society of Breast Cancer Specialists (EUSOMA) and the International Society of Geriatric Oncology (SIOG).Lancet Oncol. 2021; 22: e327-e340Summary Full Text Full Text PDF PubMed Scopus (41) Google Scholar One should congratulate them for this effort. Indeed, most scientific efforts seem to be diverted towards digging deeper in the understanding of the biology of cancer, leading to ambitious and costly gene expression profiling, but ironically leaving behind the majority of those with cancer, namely the older population, and the hot topic of competing risks.3Biganzoli L Battisti NML Wildiers H et al.Updated recommendations regarding the management of older patients with breast cancer: a joint paper from the European Society of Breast Cancer Specialists (EUSOMA) and the International Society of Geriatric Oncology (SIOG).Lancet Oncol. 2021; 22: e327-e340Summary Full Text Full Text PDF PubMed Scopus (41) Google Scholar, 4Kendal WS Dying with cancer: the influence of age, comorbidity, and cancer site.Cancer. 2008; 112: 1354-1362Crossref PubMed Scopus (71) Google Scholar Comorbidities increase with age, in both incidence or severity,5Piccirillo JF Vlahiotis A Barrett LB Flood KL Spitznagel EL Steyerberg EW The changing prevalence of comorbidity across the age spectrum.Crit Rev Oncol Hematol. 2008; 67: 124-132Crossref PubMed Scopus (201) Google Scholar making patients’ overall outcomes difficult to determine.4Kendal WS Dying with cancer: the influence of age, comorbidity, and cancer site.Cancer. 2008; 112: 1354-1362Crossref PubMed Scopus (71) Google Scholar Good medical practice cannot solely consider tumour biology and omit wider considerations as comorbidities. The UK National Health Service (NHS) developed the PREDICT algorithm, which became hitherto the most successful and validated algorithm to predict outcomes at 5 years for older patients, although no geriatric data for comorbidities were included.6de Glas NA Bastiaannet E Engels CC et al.Validity of the online PREDICT tool in older patients with breast cancer: a population-based study.Br J Cancer. 2016; 114: 395-400Crossref PubMed Scopus (48) Google Scholar Of note, the validity of the model could not be proven for prediction at 10 years, and there were limitations for patients aged 80 years or older stressing the impact of age on the meaningful value of temporality. Therefore, van der Plas-Krijgsman and colleagues created a refined prognostic tool using data from the FOCUS cohort, to predict 5-year recurrence, overall mortality, and other-cause mortality in patients aged 65 years and older with early-stage breast cancer. For external validation, they used a national cancer registry that was five times the size of the development set. While based on simple and very pragmatic inexpensive items covering both the disease and the host, the final PORTRET model is robust and could accurately predict the three outcome endpoints of interest in these older patients. Moreover, it seems to outperform PREDICT. These findings highlight the crucial need to factor in variables beyond the disease itself, with a capture of the geriatric health status, as it was done in the full model, which included comorbidities, functional status, polypharmacy, cognitive defects, and sensory deficiency. Whether one should consider the prediction advantage provided by PORTRET as small or significant seems immaterial. By including specific geriatric data, PORTRET was able to better discriminate than the submodel (similar to PREDICT) or the reduced model that were tested by the Dutch investigators. This finding demonstrates, first, the importance of considering other variables than the ones commonly assessed in oncology to potentially fine-tune adjuvant treatment in older patients. Second, it demonstrates that, although overall survival used in PORTRET might be too global, this outcome might still better reflect a certain quality of life or maintenance of dependence (both highly sought by the older persons) than the breast-cancer specific outcomes that are usually preferred in oncology programmes. One should stress that not a single large study of gene-expression assay validation enrolled a relevant number of older patients, if any at all. There is a growing trend to use this lack of inclusion of older patients in clinical trials to justify relegating research in this population to non-controlled data from registries or insurance programmes. This approach should be considered as a form of ageism, especially given the usual selection biases of real world data. This leads to poorer management, for example, whereby supposedly age-agnostic prognostic signatures for tailored treatments developed from such datasets lead to beneficial outcomes only for younger patients.7Kizy S Altman AM Marmor S et al.21-gene recurrence score testing in the older population with estrogen receptor-positive breast cancer.J Geriatr Oncol. 2019; 10: 322-329Summary Full Text Full Text PDF PubMed Scopus (22) Google Scholar Finally, this work appears as a culmination of previous landmark publications by the same group, highlighting the perseverance required to change mindsets through gradual demonstration, and reminding what should be a leitmotiv rule in research: evidence-based information for a relevant population. As long as the best information obtained from the tumour biology and from the patient is not reconciled in joined models, research in geriatric oncology will remain essentially partial and slightly opportunistic, not comprehensively supported by an oncology world often disconnected from reality, with very little chance to bring important and relevant changes in attitudes. Such PORTRET data should be tested with modern molecular portraits to reach a more mixed and inclusive model closer to reality. It is only this way that the fast-moving field of biology in oncology will find a realistic application to the older population, a segment of patients far from being virtual and with a clear unmet medical need. ECGB has received honoraria or consultation fees from BMS, Eli Lilly, G1 Therapeutics, Pfizer, Sandoz, and Seagen; and travel support for international meetings from AstraZeneca, Novartis, Pfizer, Pierre Fabre, Roche, and Sandoz. Development and validation of the PORTRET tool to predict recurrence, overall survival, and other-cause mortality in older patients with breast cancer in the Netherlands: a population-based studyThe PORTRET tool can accurately predict 5-year recurrence, overall mortality, and other-cause mortality in older patients with breast cancer. The tool can support shared decision making, especially since it provides individualised estimated benefits of adjuvant treatment. Full-Text PDF Open Access