Frail and elderly patients Comorbidities: influence on treatment - PowerPoint PPT Presentation

1 / 30
About This Presentation
Title:

Frail and elderly patients Comorbidities: influence on treatment

Description:

60% of new cancer cases in patients 65 years. 70% of ... here, the neonate or the octogenarian, even though no discernible systemic disease is present. ... – PowerPoint PPT presentation

Number of Views:1132
Avg rating:3.0/5.0
Slides: 31
Provided by: infover
Category:

less

Transcript and Presenter's Notes

Title: Frail and elderly patients Comorbidities: influence on treatment


1
Frail and elderly patientsCo-morbidities
influence on treatment
  • D. Schrijvers, MD, PhD
  • Ziekenhuisnetwerk Antwerpen-Middelheim
  • Antwerp, Belgium

2
Cancer epidemiologyCancer burden
  • Changing demographics
  • Increase in number of elderly
  • 2030 20 of the population gt 65 years (USA)
  • Cancer disease of the elderly
  • 60 of new cancer cases in patients gt 65 years
  • 70 of cancer mortality in patients gt 65 years
  • Prostate
  • Incidence 75 in patients gt 65 years
  • Mortality 92 in patients gt 65 years
  • Breast
  • Incidence 47 in patients gt 65 years
  • Mortality 58 in patients gt 65 years
  • Cancer burden will increase in elderly

3
Cancer epidemiologyProblems in cancer patients
  • Age
  • Geriatric syndromes
  • Malnutrition/urinary incontinence/visual and
    hearing impairment/gait, motility and balance
  • Polypharmacy
  • Depressive disorders
  • Frailty
  • Age-related decrease in functioning
  • Physical
  • Cognitive
  • Disabilities limitation in functional status
  • Self-reliance in daily living
  • Co-morbid conditions
  • Cardiovascular disease
  • Respiratory disease
  • Endocrine disease
  • 80 of patients gt 65 years 1 or more chronic
    disease

4
Problems in elderly cancer patientsDistribution
of co-morbidity, disability, and geriatric
syndromes
Prostate cancer (n324, mean age 79, 3, 12)
Breast cancer (n 952, mean age 76.6, 26.4)
Koroukian 2006
5
Importance of co-morbidity

6
Importance of co-morbidityLife expectancy in
relation to health status
  • Age (years) Life expectancy (years) (women/men)
  • Healthy Average Sick
  • 65 20.0/15.9 18.5/14.9 9.7/8.5
  • 70 15.8/12.5 14.8/11.8 8.6/7.4
  • 75 12.1/9.5 11.5/9.1 7.3/6.2
  • 80 8.8/7.0 8.4/6.8 5.9/4.5
  • 85 6.1/5.0 5.9/4.9 4.5/3.8
  • Extermann 2005

7
Importance of co-morbidity Prevalence and age
trends for selected co-morbidities
Holmes 2003
8
Importance of co-morbidityCo-morbidity in
relation to age in cancer patients
  • Co-morbidity Age (years) ( of population)
  • 50-59 60-74 gt75
  • None 55 35 26
  • Previous cancer 7 12 16
  • COPD 8 15 16
  • Heart diseases 6 15 19
  • Vascular disease 2 5 6
  • Hypertension 9 16 16
  • CVA/hemiplegia 1 4 6
  • Diabetes mellitus 4 8 10
  • Coeberg 1999

9
Importance of co-morbidityCo-morbidity burden in
cancer patients
Study Miles Yanick Cancer type
Lung Colorectal Median number of
co-morbidities 2 3.6-4.2 Cardiovascular
() 60 63 Respiratory () 35 16 Gastro-intes
tinal () 32 22 Genito-urinary
() 27 Osteoarticular () 21 18 Diabetes
() 11 Psycho-neuro () 5 Hematological
() 37
10
Evaluation of co-morbidity

11
Evaluation of co-morbidityCharlson co-morbidity
index
  • Index 1
  • Chronic obstructive pulmonary diseases
  • Cardiovascular diseases
  • myocardial infarction, cardiac decompensation,
    angina pectoris, peripheral arterial disease,
    intermittent claudication, abdominal aneurysm
  • Cerebrovascular diseases
  • cerebrovascular accident
  • Hypertension (medically treated)
  • Diabetes mellitus
  • Auto-immune disease
  • Peptic ulceration
  • Dementia
  • Liver function disturbances
  • Charlson 1987

Index 2 Hemiplegia Kidney function disturbances
(moderate/severe) Diabetes mellitus with terminal
organ damage Tumours solid tumours, leukemia,
lymphoma Index 3 Liver function disturbances
(moderate/severe) Index 6 AIDS Metastatic
cancer
12
Evaluation of co-morbidityOther scales
  • Charlson Comorbidity index adapted to the
    International Classification of Diseases (ICD-9)
  • Chronic Disease Score co-morbidity based on
    current medication use
  • List of co-morbid condition by the National
    Institute or Aging and National Cancer Institute
  • Geriatric assessment scale

13
Co-morbidity and prognosis

14
Co-morbidity and prognosisInfluence on survival
  • Charlson Index score 1-year survival rate ()
  • 0 88
  • 1-2 74
  • 3-4 48
  • gt 5 15
  • Charlson 1987

15
Co-morbidity and prognosisInfluence on survival
in breast cancer patients
3-year mortality in 936 patients in relation to
stage and co-morbidity
Satariano et. al. 1994
16
Co-morbidity and prognosisInfluence on survival
in cancer patients
Type co-morbidity 5-year survival
NSCLC Breast Colon Rectum Age (years)
gt 70 gt 70 lt80 gt 80 lt80 gt80 Loc Non-loc
None 41 21 67 51 40 49 37 Cardiovascular 41
31 42 38 23 28 21 COPD 21 23 51 37 31 36 29 Dia
betes mellitus 19 10 41 46 32 37 20 Previous
cancer 25 18 49 39 36 49 22 3-year
survival 1-year survival
Coebergh 2004
17
Co-morbidity and prognosisInfluence on survival
in cancer patients
Read 2004
18
Co-morbidity and treatment

19
Co-morbidity and treatmentSurgery
  • ASA classification
  • Class I The patient has no organic,
    physiologic, biochemical, or psychiatric
    disturbance. The pathologic process for which
    the operation is to be performed is localized and
    does not entail a systemic disturbance.
  • Class II Mild to moderate systemic disturbances
    caused by the conditon to be surgically treated
    or the pathophysiologic processes. The extremes
    of age are included here, the neonate or the
    octogenarian, even though no discernible
    systemic disease is present. Extreme obesity and
    chronic bronchitis also are included in this
    category.
  • Class III Severe systemic disturbance or
    disease from whatever cause, even though it may
    not be possible to firmly define the degree of
    disability.
  • Class IV Indicative of the patient with severe
    systemic disorders that are already
    life-threatening and not always correctable by
    an operation.
  • Class V The moribund patient who has little
    chance of survival but who has submitted to
    operation in desperation. Most of these patients
    require an operation as a resuscitative measure
    with little, if any, anesthesia.
  • Emergency Operation (E) Any patient in classes I
    through V who is operated on as an emergency is
    considered to be in poor physical condition. The
    letter E is placed beside the numerical
    classification.

20
Co-morbidity and treatmentSurgery
  • Goldman Criteria for Predicting Postoperative
    Cardiac Complications
  • Criteria Point Value
  • S3 gallop or jugular-vein distention on
    preoperative examination 11
  • Myocardial infarction in the preceding 6
    months 10
  • Rhythm other than sinus, or premature atrial
    contractions on 7
  • preoperative electrocardiogram
  • gt5 premature ventricular contractions/min
    documented at any 7
  • time before operation
  • Age gt70 years 5
  • Emergency operation 4
  • Important valvular aortic stenosis 3
  • Intraperitoneal, intrathoracic, or aortic
    operation 3
  • Poor general medical condition 33
  • P 2 lt 60 or P 2 gt 50 mm Hg, K lt 3.0 or Cr gt
    3.0 mg/dL, abnormal SGOT, signs of chronic liver
    disease, or patient bed ridden from non-cardiac
    causes

21
Co-morbidity and treatmentSurgery
  • Goldman Criteria for Predicting Postoperative
    Cardiac Complications
  • Class Point Total No or Only Minor
    Complication Life-Threatening Complication Cardiac
  • Death
  • I 05 99 0.7 0.2
  • II 612 93 5 2
  • III 1325 86 11 2
  • IV 26 22 22 56

22
Co-morbidity and treatmentSurgery
  • Possum

Copeland, 2002
23
Co-morbidity and treatmentChemotherapy
  • Agent Special Considerations in relation to
    co-morbidity
  • Anthracyclines Avoid use of doxorubicin in
    patients with an EF lt50.
  • Cyclophosphamide Elimination decreased in
    patients with impaired renal function
  • Methotrexate Dose adjustments based on renal
    function
  • Patients with pleural effusions and ascites at
    risk for prolonged drug elimination and toxicity
  • Fluorouracil Fluorouracil-induced cardiac
    toxicity
  • Vinca alkaloids Monitor carefully for neuropathy
  • Taxanes Hepatic impairment increases toxicity
  • Trastuzumab Cardiotoxicity

24
Co-morbidity and treatmentDrug- drug interactions
  • Agent Special Considerations in relation to
    co-medication
  • Capecitabine Increased effect of warfarin,
    decreased metabolisation of phenytoin
  • due to interference of CYP2C9
  • Fluorouracil Activation inhibited by allopurinol
  • Methotrexate Increased toxicity with
    non-steroidal anti-inflammatory drugs,
  • sulfonamides, trimethoprim
  • Cytarabine Elimination decreased by nephrotoxic
    drugs
  • Carboplatin Decreases phenytoin level
  • Cisplatin Other nephrotoxic drugs, decreases
    phenytoin level
  • Cyclophosphamide Increased effect of warfarine,
    decreases digoxin level, increased
  • metabolisation by cytochrome P450 inducers
  • Procarbazine Increased adverse effects by
    ethanol, sympatohomimetics, tricyclic
  • anti-depressants, opiates, antihypertensive
    drugs
  • Temozolomide Clearance reduced by valproic acid
  • Inducers of cytochrome P450 e.g. dexamethasone,
    carbamazepine, rifampicin, phenobarbital,
    phenytoin. Substrates of P450 e.g. simvastatin,
    cyclosporine, triazolobenzodiazepines,
    carbamazepine, dihydropyridine calcium channel
    blockers, fentanyl, warfarin.

25
Co-morbidity and treatmentDrug- drug interactions
  • Agent Special Considerations in relation to
    co-medication
  • Docetaxel Metabolisation changed by drugs
    influencing cytochrome P450 3A4
  • Paclitaxel Metabolisation changed by drugs
    influencing cytochrome P450 3A4,
  • clearance decreased when platinum coumpounds are
    given before
  • Vinblastine Metabolisation changed by drugs
    influencing cytochrome P450 3A4,
  • decreases phenytoin level
  • Vincristine Metabolisation changed by drugs
    influencing cytochrome P450 3A4,
  • decreases digoxin and phenytoin level
  • Vinorelbine Metabolisation changed by drugs
    influencing cytochrome P450 3A4
  • Etoposide Increases effect of warfarine
  • Irinotecan Metabolisation changed by drugs
    influencing cytochrome P450 3A4,
  • increases effect of warfarine
  • Inducers of cytochrome P450 e.g. dexamethasone,
    carbamazepine, rifampicin, phenobarbital,
    phenytoin. Substrates of P450 e.g. simvastatin,
    cyclosporine, triazolobenzodiazepines,
    carbamazepine, dihydropyridine calcium channel
    blockers, fentanyl, warfarin

26
Co-morbidity and treatmentDrug- drug interactions
  • Agent Special Considerations in relation to
    co-medication
  • Tamoxifen Potentiates effect of warfarin
  • Exemestane Metabolisation changed by drugs
    influencing cytochrome P450 3A4
  • Inducers of cytochrome P450 e.g. dexamethasone,
    carbamazepine, rifampicin, phenobarbital,
    phenytoin. Substrates of P450 e.g. simvastatin,
    cyclosporine, triazolobenzodiazepines,
    carbamazepine, dihydropyridine calcium channel
    blockers, fentanyl, warfarin

27
Co-morbidity in cancer patientsFlow sheet
  • Frailty
  • Disability
  • gt 3 co-morbidities
  • Geriatric syndrome
  • Life expectancy based on
  • Age
  • Co-morbidity

-

Life expectancy gt cancer survival
Life expectancy lt cancer survival
Contra-indications anti-cancer treatment
Cancer influences QoL
No influence of cancer on QoL

-
Risk and benefits anti-cancer treatment IADL Nutri
tional status Social structure
Palliative care
Follow up
Risks lt Benefits
Risks gt Benefits
Anti-cancer treatment
28
Co-morbidity in cancer patientsConclusions
  • Cancer patients should receive optimal
    anti-cancer treatment in relation to
  • Life expectancy
  • Improvement of quality of life
  • Treatment should be adapted to
  • Co-morbidity status
  • Disabilities
  • Geriatric syndromes
  • Co-medication

29
Co-morbidity in cancer patientsFuture questions
  • Co-morbidity assessment
  • Patient selection for anti-cancer treatment based
    on co-morbidities, disabilities and geriatric
    syndromes
  • Predictive models for side effects

30
(No Transcript)
Write a Comment
User Comments (0)
About PowerShow.com