Interprofessional Webinar Series

Transcription

1 Interprofessional Webinar Series

2 Prognostication I: Improving Accuracy to Support Care and Hospice Access Pauline Lesage, MD, LLM Physician Educator MJHS Institute for Innovation in Palliative Care

3 Disclosure Slide Pauline Lesage, MD, LLM, has no financial arrangements or affiliations with any commercial entities whose products, research or services may be discussed in these materials. Any discussion of investigational or unlabeled uses of a product will be identified. Russell K. Portenoy, MD, Planner, has indicated a relationship with the following: Pfizer Inc. No other Planning Committee Member has any disclosures.

4 Prognostication in Advanced Cancer Patients Introduction Illness trajectories Formulation prognosis: Clinician estimate of survival (CES) Performance status Symptoms Quality of life Biologic parameters Prognostic scores and models Hospice: determining Terminal Status

5 Prognostication is not a certainty but a way to respond to our quest of knowing what is ahead and planning for it.

6 Predicting Survival In Advanced Cancer 1 Why prognosticate? Answer patients questions with reasonable certainty Help patients develop insight into their illness Select the most appropriate setting of care Give proportionate care (i.e., chemotherapy) and minimize the risks of under- or overtreatment Communicate between different medical teams with objective information Offer timely palliative care and hospice enrollment 1 Lamont. Epidemiology and Prognostication in Advanced Cancer. Section II Issues in Palliative Care

7 Do patients want to know? 2 Studies show that most patients want to be given prognostic information. They rate this information as both important to them and necessary. 2 Hagerty. Communicating prognosis in cancer care: a systematic review of the literature. Annals of Oncology 16: , 2005

8 Illness Trajectory: The Continuum of Palliative Care Illness trajectory Adapted from the Canadian Palliative Care Association. Towards a consensus in standardized principles of practice. 1995

9 Prognostication in Advanced Cancer 1,3 Disease Specific Stage IV Breast Cancer - Tumor characteristics - Receptor status -Cancer Age Early - Disease cancer stage (TNM) Stage IV Colon Cancer Stage IV Gastric Cancer Stage IV or recurrent Head and Neck Stage IIIb or IV Lung Cancer Hepatocellular Carcinoma Pancreatic Adenocarcinoma Median Survival in untreated patients 1.5 years 5 months 5 months 4 months 5-6 months 1 month Advanced Cancer 3 months - Performance status - Anorexiacachexia - Lymphopenia - Quality of life 1 Lamont. Epidemiology and Prognostication in Advanced Cancer. Section II Issues in Palliative Care Lamont. Complexities in prognosticating in advanced cancer. JAMA 2003, Vol. 290, No. 1

10 Illness Trajectories SUDDEN DEATH 33% 8% 25% 33% DEMENTIA

11 Formulating Prognosis: CES Clinician estimate of survival (CES) Performance status Symptoms Quality of life Biologic parameters Prognostic scores and models

12 CES: Are we good at clinically estimating a patient s prognosis? 3 Multiple studies Physician estimate of survival incorrect by a factor of 3 to 5 Almost always optimistic Inaccurate in at least 30% of cases 3 Lamont. Complexities in prognosticating in advanced cancer. JAMA 2003, Vol. 290, No. 1

13 Why are physicians not using prognostic tools? 6 I was not exposed to them during medical school They are time consuming They are difficult to remember and cumbersome Not valid No limitation 6 Zanartu C. Matti-Orozco B. Use of prognostic tools in the hospital, assessment of factors behind their use or lack thereof through a physician-oriented survey. Am J Hosp Palliat Care 2013 Sep 26. [Epub ahead of print]

14 The Role of the disinterested physician 4 Concept of a disinterested clinician, with less patient contact, less personal investment in outcome, may give more accurate prognoses 4 Christakis. Extent and determinants of error in doctors' prognoses in terminally ill patients: prospective cohort study. BMJ 2000; 320:

15 Formulating Prognosis: Performance Status Clinician estimate of survival (CES) Performance status Symptoms Quality of life Biologic parameters Prognostic scores and models

16 Performance Status 1 A global measure of a patient s functional capacity Most extensively studied Consistently found to predict survival in cancer patients Examples: Karnofsky, PPS, ECOG 1 Lamont. Epidemiology and Prognostication in Advanced Cancer. Section II Issues in Palliative Care

17 Karnofsky Performance Status Scale 7 No evidence of disease 90 Normal activity with effort, some signs or sym Minor signs or symptoms of disease Occasional assistance, but ile to care for most needsrequires considerable assistance and medical Requires hospitalization alth 30 ough death is not imminent Active supportive treatment n 10 Moribund, fatal processes progressing rapidly Dead 7 Karnofsky. The Use of Nitrogen Mustard in the Palliative Treatment of Carcinoma. Cancer, 1, 1948, p 635

18 Karnofsky Performance Status Scale

19 Relation between KPS and life expectancy In hospice patients 8 : >50%: 12 weeks 30-40%: Median Survival = 7 weeks 10-20%: Median Survival = 2 weeks In advanced cancer patients 9 : >50%: Median Survival = 7-13 weeks 30-40%: Median Survival = 1-7 weeks 10-20%: Median Survival = 1-2 weeks In palliative care patients 10 : <50s: Median survival < 8 weeks 8 Reuben DB, Mor V, Hiris J. Clinical symptoms and length of survival in patients with terminal cancer. Arch Intern Med 1988; Loprinzi. Prospective evaluation of prognostic variables from patient-completed questionnaires. Clin Onc 1994; 12: Evans. Prognostic uncertainty in terminal care: can the Karnofsky index help? Lancet. 1985;1(8439):1204

20 Other performance status scores ECOG 11 : Eastern Cooperative Oncology Group Predictive of survival in both advanced and terminal cancer 11 Oken. Toxicity And Response Criteria Of The Eastern Cooperative Oncology Group. Am J Clin Oncol 5: , 1982

21 Karnofsky and ECOG equivalency

22 Palliative Performance Scale A modification of the KPS Ambulation, activity level, evidence of disease, self-care, intake level, level of consciousness 12 Anderson. Palliative Performance Scale: A new tool. Journal of Palliative Care (1) 5-11

23 Formulating Prognosis: Symptoms Clinician estimate of survival (CES) Performance status Symptoms Quality of life Biologic parameters Prognostic scores and models

24 Clinical Symptoms and Length of Survival in Advanced Cancer Index Anorexia17, 18, 19, 20 < Confusion20, 21 < Dysphagia 18 Dyspnea17, 18, 22 < Xerostomia 21 Median Survival 58 days 38 days < 30 days 30 days < 50 days 17 Reuben. Clinical symptoms and length of survival in patients with terminal cancer. Arch Intern Med 1988:148: Maltoni. Prediction of survival of patients terminally ill with cancer. Results of an Italian prospective multicentric study. Cancer May 15;75(10): Pirovano. A new palliative prognostic score: a first step for the staging of terminally ill cancer patients. Italian Multicenter and Study Group on Palliative Care. J Pain Symptom Manage Apr;17(4): Llobera. Terminal cancer. duration and prediction of survival time. Eur J Cancer Oct;36(16): Tamburini. Prognostic value of quality of life scores in terminal cancer patients. J Pain Symptom Manage Jan;11(1): Hardy. Prediction of survival in a hospital-based continuing care unit. Eur J Cancer. 1994;30A(3):284-8

25 Formulating Prognosis: QOL Clinician estimate of survival (CES) Performance status Symptoms Quality of life Biologic parameters Prognostic scores and models

26 QOL & Survival Distress as a marker of survival 23 : Symptom distress score correlated with survival in Lung Cancer Patients. Quality of life as a better marker of survival than tumor size 24 : Distress elicited by physical symptoms 25 : Using the Memorial Symptom Assessment Scale Independent marker of survival 23 Degner. Symptom distress in newly diagnosed ambulatory cancer patients and as a predictor of survival in lung cancer. J Pain Symptom Manage Aug;10(6): Earlam. Relation between tumor size, quality of life, and survival in patients with colorectal liver metastases. JCO January 1996 vol. 14 no Chang. Quality of life and survival. Cancer

27 Formulating Prognosis: Biologic Parameters Clinician estimate of survival (CES) Performance status Symptoms Quality of life Biologic parameters Prognostic scores and models

28 Biological Parameters and Survival Platelet count elevation 26 Decreased serum albumin Lymphocyte count 27 Albumin Sodium Alkaline Phosphatase High total WBC count 28 Low lymphocyte percentage Low pseudocholinesterase Serum albumin < 2.5 gm/dl 29 Serum albumin Janisch. Prognostic factors for survival in patients treated in phase I clinical trials. Cancer 74.7 (1994): Muers. Prognosis in lung cancer: physicians' opinions compared with outcome and a predictive model. Thorax 51.9 (1996): Maltoni. Biological indices predictive of survival in 519 Italian terminally ill cancer patients. Journal of pain and symptom management 13.1 (1997): National Hospice and Palliative Care Organization Herrmann. Serum albumin level on admission as a predictor of death, length of stay, and readmission. Archives of Internal Medicine (1992): 125

29 Formulating Prognosis: Prognostic Scores/Models Clinician estimate of survival (CES) Performance status Symptoms Quality of life Biologic parameters Prognostic scores and models

30 Prognostic Scores and Models Palliative Prognostic Score (PaP Score) Palliative Prognostic Index (PPI) SUPPORT Study Terminal Cancer Syndrome GBU Index Australian Study

31 PaP Score An exponential multiple regression model Evaluate joint effect of clinico-biologic variables on survival Numerical score given to each variable Subscores are summed Readily calculable at the bedside Highly predictive of short-term survival (30 days) 32 Maltoni, Marco, et al. Successful validation of the palliative prognostic score in terminally ill cancer patients. Journal of pain and symptom management 17.4 (1999):

32 PaP Score

33 Survival PaP score curve 1 Group A.5 Group B 0 Group C Days 32 Maltoni, Marco, et al. Successful validation of the palliative prognostic score in terminally ill cancer patients. Journal of pain and symptom management17.4 (1999):

34 Palliative Prognostic Index (PPI) 33 Morita T and al. The Palliative Prognostic Index: A scoring system for survival prediction of terminally ill cancer patients. Supportive Care Cancer 1999; 7:82-86

35

36 Palliative Prognostic Index (PPI) PPI predictive of 3 weeks survival: 83% sensitivity 85% specificity 33 Morita T and al. The Palliative Prognostic Index: A scoring system for survival prediction of terminally ill cancer patients. Supportive Care Cancer 1999; 7:82-86.

37 Hospice guidelines (prognosis <6 months) Certification for Hospice shall be based on the physician s or medical director s clinical judgment regarding the normal course of the individual s illness Individual prognosis is for a life expectancy of 6 months or less if the terminal illness runs its normal course Public Health Law 42 chap. 4 Part 418.2

38 Hospice LCD (Local Coverage Determination): Determining terminal illness Decline in clinical status guidelines Non-disease specific baseline guidelines Disease Specific Guidelines LCD: Decisions by Medicare and their administrative contractors to provide coverage information on services offered by participating providers. They are guidelines.

39 Hospice LCD: Decline in clinical status guidelines Progression of disease documented by: Worsening of clinical status, symptoms, signs, laboratory findings Decline in Karnofsky Performance status History of increased ER visits, hospitalizations, MD visits related to hospice diagnosis

40 Hospice LCD: Non-disease specific guidelines Impairment in functional status (KPS or PPS <70%) Dependence/assistance on 2 or > of ADLs: Co-morbidities: Chronic Obstructive Pulmonary Disease, congestive heart failure, Ischemic Heart Disease, Diabetes Mellitus, neurologic disease, renal failure, liver failure, neoplasia, Acquired Immune Deficiency Syndrome, dementia, refractory severe autoimmune disease

41 Hospice LCD: Disease specific guidelines Cancer Disease with metastases at presentation, or Progression from an earlier stage to metastatic disease with either: Continued decline in spite of therapy, or Patient declines further disease directed therapy

42 Conclusions Physicians prognostic estimates are a central element of both patient and physician decision-making, especially at the end of life. Physicians prognostic estimates in their terminally ill patients are often wrong and usually optimistic.

43 Conclusions (Cont d) In end stage cancer, general markers of frailty (poor PO intake, weight loss, immobility) are reliable prognostic variables. A patient with advanced cancer that is disabled will most likely live less than 8 weeks. The development of improved clinical prediction tools will help abate the systematic optimism in formulating and communicating prognoses.

44 Prognostication I: Improving Accuracy to Support Care and Hospice Access Q/A

45 Bibliography 1. Lamont. Epidemiology and Prognostication in Advanced Cancer. Section II Issues in Palliative Care Hagerty. Communicating prognosis in cancer care: a systematic review of the literature. Annals of Oncology 16: , Lamont. Complexities in prognosticating in advanced cancer. JAMA 2003, Vol. 290, No Christakis. Extent and determinants of error in doctors' prognoses in terminally ill patients: prospective cohort study. BMJ 2000; 320: LaMont. Prognostic disclosure to Patients with Cancer Towards the End of Life. Ann Intern Med : Zanartu C. Matti-Orozco B. Use of prognostic tools in the hospital, assessment of factors behind their use or lack thereof through a physician-oriented survey. Am J Hosp Palliat Care 2013 Sep 26. [Epub ahead of print] 7. Karnofsky. The use of Nitrogen Mustard in the Palliative Treatment of Carcinoma. Cancer, 1, 1948, p Reuben DB, Mor V, Hiris J. Clinical symptoms and length of survival in patients with terminal cancer. Arch Intern Med 1988; Loprinzi. Prospective evaluation of prognostic variables from patient-completed questionnaires. Clin Onc 1994; 12: Evans. Prognostic uncertainty in terminal care: can the Karnofsky index help? Lancet. 1985;1(8439):1204

46 Bibliography 11. Oken. Toxicity And Response Criteria Of The Eastern Cooperative Oncology Group. Am J Clin Oncol 5: , Anderson. Palliative Performance Scale: A New Tool. Journal of Palliative Care (1) Virik K, Glare P. Validation of the Palliative Performance Scale for inpatients admitted to a palliative care unit in Sydney,Australia. J Pain Symp Manage. 2002; 23(6): Anderson F, Downing GM, Hill J. Palliative Performance Scale (PPS): a new tool. J Palliat Care. 1996; 12(1): Morita. Validity of the palliative performance scale from a survival perspective. J Pain Symptom Manage Jul;18(1): Lau, F, and al. Using the Palliative Performance Scale to Provide Meaningful Survival Estimates. Journal of Pain and Symptom Management, Vol.38 No.1 July 2009, p Reuben. Clinical symptoms and length of survival in patients with terminal cancer. Arch Intern Med 1988:148: Maltoni. Prediction of survival of patients terminally ill with cancer. Results of an Italian prospective multicentric study. Cancer May 15;75(10): Pirovano. A new palliative prognostic score: a first step for the staging of terminally ill cancer patients. Italian Multicenter and Study Group on Palliative Care. J Pain Symptom Manage Apr;17(4): Llobera. Terminal cancer. duration and prediction of survival time. Eur J Cancer Oct;36(16):

47 Bibliography 21. Tamburini. Prognostic value of quality of life scores in terminal cancer patients. J Pain Symptom Manage Jan;11(1): Hardy. Prediction of survival in a hospital-based continuing care unit. Eur J Cancer. 1994;30A(3): Degner. Symptom distress in newly diagnosed ambulatory cancer patients and as a predictor of survival in lung cancer. J Pain Symptom Manage Aug;10(6): Earlam. Relation between tumor size, quality of life, and survival in patients with colorectal liver metastases. JCO January 1996 vol. 14 no Chang. Quality of Life and Survival. Cancer Janisch. Prognostic factors for survival in patients treated in phase I clinical trials. Cancer 74.7 (1994): Muers. Prognosis in lung cancer: physicians' opinions compared with outcome and a predictive model. Thorax 51.9 (1996): Maltoni. Biological indices predictive of survival in 519 Italian terminally ill cancer patients. Journal of pain and symptom management 13.1 (1997): National Hospice and Palliative Care Organization Herrmann. Serum albumin level on admission as a predictor of death, length of stay, and readmission. Archives of Internal Medicine (1992): 125

48 Bibliography 31. Knaus, William A., et al. The SUPPORT prognostic model: objective estimates of survival for seriously ill hospitalized adults. Annals of Internal Medicine (1995): Maltoni, Marco, et al. Successful validation of the palliative prognostic score in terminally ill cancer patients. Journal of pain and symptom management17.4 (1999): Morita T and al. The Palliative Prognostic Index: A scoring system for survival prediction of terminally ill cancer patients. Supportive Care Cancer 1999; 7: Viganò, Antonio, Eduardo Bruera, and Maria E. Suarez-Almazor. Terminal cancer syndrome: myth or reality?. Journal of palliative care 15.4 (1999): Sloan, Jeff A., et al. A simple stratification factor prognostic for survival in advanced cancer: the good/bad/uncertain index. Journal of clinical oncology19.15 (2001): Rosenthal, Mark A., et al. Prediction of life-expectancy in hospice patients: identification of novel prognostic factors. Palliative medicine 7.3 (1993): Chow, Edward, et al. Predictive model for survival in patients with advanced cancer. Journal of Clinical Oncology (2008): Feliu, Jaime, et al. Development and validation of a prognostic nomogram for terminally ill cancer patients. Journal of the National Cancer Institute (2011): Soares M et al. Effect of age on survival of critically ill patients with cancer. Crit Care Med. 2006;34: Azoulay et al. The intensive care support of patients with malignancy: do everything that can be done. Intensive care medicine 32.1 (2006): Groeger, Jeffrey S., et al. Multicenter outcome study of cancer patients admitted to the intensive care unit: a probability of mortality model. Journal of clinical oncology 16.2 (1998):