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Case report: Poor prognosis or poor prognostication?

Published online by Cambridge University Press:  31 October 2024

Jacqueline Tschanz*
Affiliation:
Department of Palliative Care, Rehabilitation, and Integrative Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, US
Rida Khan
Affiliation:
Department of Palliative Care, Rehabilitation, and Integrative Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, US
Eduardo Bruera
Affiliation:
Department of Palliative Care, Rehabilitation, and Integrative Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, US
*
Corresponding author: Jacqueline Tschanz; Email: [email protected]
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Abstract

Objectives

This case highlights the limitations of current prognostication and communication in clinical practice.

Methods

We report a case of a 50 year old patient with metastatic melanoma following admission to intensive care unit and later transferred to palliative care unit for end-of-life care.

Results

The patient had clinical improvement despite signs of predictors of death and was later transferred back to care of oncology team.

Significance of results

Physicians frequently overestimate or underestimate survival time which can be distressing to patients and families. There is need for further research to improve the accuracy of these tools for the sake of our patients and their families.

Type
Case Report
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press.

Introduction

Although prognostication for survival can be challenging, this information can be critical to helping patients and families make plans. Despite how difficult this survival prognostication can be, research has shown that patients and their families want as much information as clinicians are able to provide. Most patients with advanced cancer want to know their prognosis including survival time(Enzinger et al. Reference Enzinger, Zhang and Schrag2015; Hagerty et al. Reference Hagerty, Butow and Ellis2004; Umezawa et al. Reference Umezawa, Fujimori and Matsushima2015). Caregivers of patients at end of life have been shown to want more information about the process communicated to them (Sercekus Reference Serçekuş, Besen and Günüşen2014).

Clinician prediction of survival is the most common approach and is generally approached in 3 ways: (1) temporal approach (how long will the patient live?) (2) the surprise question (would I be surprised if the patient died by [time]?), and probabilistic approach (what is the probability the patient will live until [time]?) (Perez-Cruz et al. Reference Perez-Cruz, Dos Santos and Silva2014). There are various scoring tools physicians have used to try to assist with end-of-life prognostication such as Palliative Performance Scale (PPS), Palliative Prognostic Index, Palliative Prognostic Score, Glasgow Prognostic Score have been used most frequently. Unfortunately, these systems are not always accurate and are not routinely used in clinical practice.

Death within 3 days can be more accurately diagnosed, generally assessed with physical exam findings including pulselessness, mandibular breathing, hyperextension of neck, death rattle, Cheyne-stokes breathing, and drooping of the nasolabial folds (Hui et al. Reference Hui, Hess and Dos Santos2015; Mori et al. Reference Mori, Morita and Bruera2022).

Systematic reviews have shown physicians tend to overestimate survival (Cheon et al. Reference Cheon, Agarwal and Popovic2016). Providing incorrect prognosis for patients can be distressing for patients and caregivers. In the following case, the patient was given a predicted survival but had an unexpected outcome.

Case

A man in his 50’s with metastatic melanoma which has progressed through multiple lines of therapy and found to have metastatic disease to brain presented to a tertiary care center for a second opinion. The patient arrived by car at the cancer center for an outpatient visit, but he had a seizure en-route. He became unconscious with clonic movements of his limbs. He was then seen in the emergency department of the cancer center. Despite the use of a benzodiazepine, steroids, and levetiracetam, the patient remained unresponsive and was transferred to the intensive care unit. Brain imaging showed metastatic lesions causing a midline shift and entrapment of a portion of the temporal lobe. After further treatment did not lead to recovery, the patient’s wife was told he would not be a candidate for further therapy and transfer to the palliative care unit (PCU) for comfort care was recommended.

Prior to transfer to the PCU, the patient was on dexamethasone 4 mg every 6 hours. In the PCU the patient had flattening of his nasolabial folds and continued to be unresponsive. Patient was continuing to have seizures requiring lorazepam, however his wife wanted less use of the sedating medication and medical team thus tried more aggressive steroid dose of 12 mg of dexamethasone twice daily. A family meeting was held with physician and multidisciplinary team of a counselor and a chaplain to help support her and communicate the patient’s imminent death based on the flattening of his nasolabial folds and PPS of 10.

Initial week in the PCU was uneventful requiring little symptom manage as patient was unresponsive. However, the patient progressively regained consciousness in the week that followed. After 2 weeks in the PCU, he had the energy to sit up and was eating solid food. The melanoma team was reconsulted to assess for treatment candidacy. Repeat magnetic resonance imaging showed decrease in swelling around tumors and resolution of prior midline shift. The patient was transferred out of the PCU and treated under the care of oncology teams for several months.

Discussion

This case highlights that prognostication, even when backed by scientific studies, is not always accurate. A prior study has shown that doctors overestimate the time a patient has remaining (Cheon et al. Reference Cheon, Agarwal and Popovic2016), but this case showcases an example of experienced palliative care specialists underestimating the prognosis. The uncertainty regarding survival can be distressing to family members who are trying their best to process the condition of a loved one while simultaneously making the necessary arrangements (Hui et al. Reference Hui, Paiva and Del Fabbro2019).

In our case, the patient was determined to be imminently dying based on the low PPS and flattening of nasolabial folds. These findings have been shown to be indicative of death in less than 3 days in 94% of cases (Hui et al. Reference Hui, Hess and Dos Santos2015). Prognostication in cancer can be particularly difficult. Patients who die of diseases related to organ failure such as CHF, COPD, or CKD have markers of the function of the organ that can assist in prognosis and show decline. Cancer patients tend to die of complications, most frequently, sepsis, thrombosis, or arrhythmias without warnings of decline (Bruera et al. Reference Bruera, Chisholm and Dos Santos2015). The nature and onset of those complications cannot be predicted by tumor mass. Another major reason for difficulty in prognosis is the continuous improvement in cancer therapies (Larkin et al. Reference Larkin, Chiarion-Sileni and Gonzalez2019). Prognosis for malignant melanoma has changed greatly in the last decade from medial survival of 11 months in 2013 to 24 months in 2021 (van Not et al. Reference van Not, van den Eertwegh and Haanen2024). This blurring of therapeutic limits is occurring for multiple hematological and solid tumors (Knight et al. Reference Knight, Karapetyan and Kirkwood2023). When our team reconsulted the melanoma oncologists they concluded that the patient might benefit from further treatment. One of the advantages of palliative care teams in acute care facilities is the seamless interaction with specialists that make consultation much less difficult for the patient and family as compared to hospice revocation.

Our patient later clinically improved and revoked comfort care while in the PCU, electing to pursue more treatment offered by the melanoma team. One study showed that around 18% of patients who are discharged from hospice do so to resume disease directed therapy (Russell et al. Reference Russell, Diamond and Lauder2017). Discharge from hospice can be a difficult experience for patients and caregivers (Wu and Volker Reference Wu and Volker2019). Though our patient was able to pursue disease directed therapy after electing comfort care, one study showed that patients who choose to revoke hospice to pursue treatment have higher mortality rates in the next 6 months following revocation (LeSage et al. Reference LeSage, Borgert and Rhee2014). Another study showed that aggressive medical treatment at end of life was associated with worse caregiver bereavement (Wright et al. Reference Wright, Zhang and Ray2008). Improving our existing survival prognostic models might prevent this kind of distress for patients and families.

Physicians who care for patients toward the end of life are experienced in keeping families updated day to day, as clinical status can change quickly and without notice. Current prognostic models can help guide discussion with family members, but physicians need to be aware of the risk of the anchoring bias, in which the medical team only makes decisions based on the initial presented information, rather than reevaluating the situation completely even when things do not go as expected (Rehana and Huda Reference Rehana and Huda2021). Continuously reassessing day to day and keeping families updated is of vital importance. A bias toward palliative care is less common (Erel et al. Reference Erel, Marcus and Dekeyser-Ganz2022), but as this case highlights, is still possible.

A number of studies have shown the need for better communication for families from the medical team at this delicate time. Some of the issues family members had include not receiving an explanation for how long the patient and family could talk and having a feeling of uncertainty caused by vague explanations about future changes (Mori et al. Reference Mori, Morita and Bruera2022). Though the inaccuracies can be distressing, forgoing these survival prognostic models completely is also not the answer. Not giving family members a chance to prepare for the patient’s death could result in a sense of having unfinished business, which leads to higher depression and grief scores (Mori et al. Reference Mori, Morita and Bruera2022).

Uncertainty in prognosis cannot be helped, however there are actions the medical team can take to mitigate the effects of uncertainty for family members. For instance, it is common practice at our institution to use large margins in our temporal and percentage estimations due to this uncertainty (Cheon et al. Reference Cheon, Agarwal and Popovic2016), including phrases like “hours to days” and “days to weeks.” Once patients have elected for comfort care, we do not pursue invasive measures, like labs or imaging, which could potentially help diagnose any complications that come up. Instead, we assure the patient and family members that we will manage any distress that is the consequence of complication with symptom management. Another important strategy is to remind caregivers that because we are imperfect at prognostication (Chen et al. Reference Chen, Chung and Lam2023), any plans or decisions need to be made immediately. Giving the caregivers this opportunity allows them to care for themselves by prioritizing their rest and nutrition so they can care for the patient better as well.

Conclusion

Survival prognostication is valuable to families. Despite the vast number of survival prognostication models available, physicians still overestimate or underestimate survival. Further research should focus on specific prognostic factors and their rate of accuracy so the existing survival prognostic models can be improved.

Author contributions

Jacqueline Tschanz and Rida Khan contributed equally.

Competing interests

The authors have no competing interests to declare.

References

Bruera, S, Chisholm, G, Dos Santos, R, et al. (2015) Frequency and factors associated with unexpected death in an acute palliative care unit: Expect the unexpected. Journal of Pain Symptom Management 49(5), 822827. doi:10.1016/j.jpainsymman.2014.10.011CrossRefGoogle Scholar
Chen, W, Chung, JOK, Lam, KKW, et al. (2023) End-of-life communication strategies for healthcare professionals: A scoping review. Palliative Medicine 37(1), 6174. doi:10.1177/02692163221133670CrossRefGoogle ScholarPubMed
Cheon, S, Agarwal, A, Popovic, M, et al. (2016) The accuracy of clinicians’ predictions of survival in advanced cancer: A review. Annals of Palliative Medicine 5(1), 2229. doi:10.3978/j.issn.2224-5820.2015.08.04Google ScholarPubMed
Enzinger, AC, Zhang, B, Schrag, D, et al. (2015) Outcomes of prognostic disclosure: Associations with prognostic understanding, distress, and relationship with physician among patients with advanced cancer. Journal of Clinical Oncology ASCO 33(32), 38093816. doi:10.1200/jco.2015.61.9239CrossRefGoogle ScholarPubMed
Erel, M, Marcus, E-L and Dekeyser-Ganz, F (2022) Practitioner bias as an explanation for low rates of palliative care among patients with advanced dementia. Health Care Analysis 30(1), 5772. doi:10.1007/s10728-021-00429-xCrossRefGoogle ScholarPubMed
Hagerty, R, Butow, P, Ellis, P, et al. (2004) Cancer patient preferences for communication of prognosis in the metastatic setting. Journal of Clinical Oncology, 22(9), 17211730. doi: 10.1200/JCO.2004.04.095CrossRefGoogle ScholarPubMed
Hui, D, Hess, K, Dos Santos, R, et al. (2015) A diagnostic model for impending death in cancer patients: Preliminary report. Cancer 121(21), 39143921. doi:10.1002/cncr.29602CrossRefGoogle ScholarPubMed
Hui, D, Paiva, CE, Del Fabbro, EG, et al. (2019) Prognostication in advanced cancer: Update and directions for future research. Supportive Care in Cancer 27(6), 19731984. doi:10.1007/s00520-019-04727-yCrossRefGoogle ScholarPubMed
Knight, A, Karapetyan, L and Kirkwood, JM (2023) Immunotherapy in melanoma: Recent advances and future directions. Cancers (Basel) 15(4), . doi:10.3390/cancers15041106CrossRefGoogle ScholarPubMed
Larkin, J, Chiarion-Sileni, V, Gonzalez, R, et al. (2019) Five-year survival with combined nivolumab and ipilimumab in advanced melanoma. New England Journal of Medicine 381(16), 15351546. doi:10.1056/NEJMoa1910836CrossRefGoogle ScholarPubMed
LeSage, K, Borgert, AJ and Rhee, LS (2014) Time to death and reenrollment after live discharge from hospice: A retrospective look. American Journal of Hospice and Palliative Medicine® 32(5), 563567. doi:10.1177/1049909114535969CrossRefGoogle ScholarPubMed
Mori, M, Morita, T, Bruera, E, et al. (2022) Prognostication of the last days of life. Cancer Research and Treatment 54(3), 631643. doi:10.4143/crt.2021.1573CrossRefGoogle ScholarPubMed
Perez-Cruz, PE, Dos Santos, R, Silva, TB, et al. (2014) Longitudinal temporal and probabilistic prediction of survival in a cohort of patients with advanced cancer. Journal of Pain Symptom Management 48(5), 875882. doi:10.1016/j.jpainsymman.2014.02.007CrossRefGoogle Scholar
Rehana, R and Huda, N (2021) A common heuristic in medicine: Anchoring. Annals of Medical & Health Sciences Research 11, 14611463.Google Scholar
Russell, D, Diamond, EL, Lauder, B, et al. (2017) Frequency and risk factors for live discharge from hospice. Journal of the American Geriatrics Society 65(8), 17261732. doi:10.1111/jgs.14859CrossRefGoogle ScholarPubMed
Serçekuş, P, Besen, DB, Günüşen, NP et al. (2014) Experiences of family caregivers of cancer patients receiving chemotherapy. Asian Pacific Journal of Cancer Prevention 15(12), . doi:10.7314/apjcp.2014.15.12.5063CrossRefGoogle ScholarPubMed
Umezawa, S, Fujimori, M, Matsushima, E, et al. (2015) Preferences of advanced cancer patients for communication on anticancer treatment cessation and the transition to palliative care. Cancer 121(23), 42404249. doi:10.1002/cncr.29635CrossRefGoogle ScholarPubMed
van Not, OJ, van den Eertwegh, AJM, Haanen, JB, et al. (2024) Improving survival in advanced melanoma patients: A trend analysis from 2013 to 2021. eClinicalMedicine 69, . doi:10.1016/j.eclinm.2024.102485CrossRefGoogle ScholarPubMed
Wright, AA, Zhang, B, Ray, A, et al. (2008) associations between end-of-life discussions, patient mental health, medical care near death, and caregiver bereavement adjustment. JAMA 300(14), 16651673. doi:10.1001/jama.300.14.1665CrossRefGoogle ScholarPubMed
Wu, S and Volker, DL (2019) Live discharge from hospice: A systematic review. Journal of Hospice & Palliative Nursing 21(6), 482488. doi:10.1097/njh.0000000000000547CrossRefGoogle ScholarPubMed