Journal of Pain and Symptom Management
Volume 36, Issue 4 , Pages 351-357, October 2008

The Prevalence of Nocturnal Hypoxemia in Advanced Cancer

  • Andrew Wilcock, DM, FRCP

      Affiliations

    • Hayward House Macmillan Specialist Palliative Cancer Care Unit, Nottingham University Hospitals NHS Trust, Nottingham
    • Corresponding Author InformationCorresponding author: Andrew Wilcock, DM, FRCP, Hayward House Macmillan Specialist Palliative Cancer Care Unit, Nottingham University Hospitals NHS Trust, City Hospital Campus, Nottingham NG5 1PB, United Kingdom.
    • ,
  • Ruth England, MRCP

      Affiliations

    • Hayward House Macmillan Specialist Palliative Cancer Care Unit, Nottingham University Hospitals NHS Trust, Nottingham
    • ,
  • Bisharat El Khoury, MRCGP

      Affiliations

    • Hayward House Macmillan Specialist Palliative Cancer Care Unit, Nottingham University Hospitals NHS Trust, Nottingham
    • ,
  • Jacky Frisby, MRCP

      Affiliations

    • Hayward House Macmillan Specialist Palliative Cancer Care Unit, Nottingham University Hospitals NHS Trust, Nottingham
    • ,
  • Paul Howard, MRCP

      Affiliations

    • Hayward House Macmillan Specialist Palliative Cancer Care Unit, Nottingham University Hospitals NHS Trust, Nottingham
    • ,
  • Sarah Bell, MRCP

      Affiliations

    • Hayward House Macmillan Specialist Palliative Cancer Care Unit, Nottingham University Hospitals NHS Trust, Nottingham
    • ,
  • CathAnn Manderson, RN

      Affiliations

    • Hayward House Macmillan Specialist Palliative Cancer Care Unit, Nottingham University Hospitals NHS Trust, Nottingham
    • ,
  • Vaughan Keeley, PhD, FRCP

      Affiliations

    • Nightingale Macmillan Unit, Derby Hospitals NHS Foundation Trust, Derby, United Kingdom
    • ,
  • William Kinnear, MD, FRCP

      Affiliations

    • Respiratory Medicine Department, Nottingham University Hospitals NHS Trust, Nottingham

Accepted 14 November 2007. published online 21 May 2008.

Article Outline

Abstract 

Nocturnal hypoxemia is associated with excessive daytime sleepiness in patients with chronic respiratory disease. This relationship has not been explored in patients with cancer. This study examined the prevalence of nocturnal hypoxemia in patients admitted to a specialist palliative care unit, and explored relationships with demographic and physiological parameters, opioid or other sedative drug use, and daytime sleepiness, fatigue, and quality of life. Demographic details, diagnosis, performance status, body mass index, opioid or other sedative drug use, hemoglobin, spirometry, and sniff nasal inspiratory pressures were obtained, along with Epworth Sleepiness Scale, Multidimensional Fatigue Inventory, and Short Form-36 health questionnaire scores. An oximeter recorded resting daytime oxygen saturation (SaO2); overnight SaO2 was recorded for a minimum of five hours. Nocturnal hypoxemia was defined as SaO2<90% for ≥2% of the monitored nighttime. Of 100 patients, 35 had nocturnal hypoxemia. These were more likely to have lung disease (P<0.05), a lower forced expiratory volume in one second % predicted (P=0.01), lower daytime SaO2 (P=0.01) and higher levels of mental fatigue (difficulty concentrating) (P=0.02), compared to those without nocturnal hypoxemia. Both groups exhibited abnormal levels of daytime sleepiness. Nocturnal hypoxemia is common in this group of patients and may contribute to mental fatigue (difficulty concentrating).

Key Words: Nocturnal hypoxemia, daytime sleepiness, fatigue, cancer, palliative care

 

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Introduction 

Fatigue is a distressing symptom experienced by 60%–95% of patients with cancer and is difficult to relieve.1, 2 New approaches are required but progress is difficult because of the subjective and nonspecific nature of fatigue, the lack of a standardized definition and diagnostic criteria, and an incomplete understanding of the pathophysiology and the coexistence of multiple possible causes. Despite these difficulties, a rational approach is to try and identify factors likely to contribute to fatigue that are amenable to treatment, for example, anemia, depression, muscle deconditioning, and undesirable effects of drugs.1, 2, 3, 4, 5

Although fatigue and daytime sleepiness are generally studied as separate entities, they may be related phenomena.6 A link exists between daytime sleepiness and nocturnal hypoxemia in patients with chronic obstructive pulmonary disease, obstructive sleep apnea, and cryptogenic fibrosing alveolitis.5, 6, 7, 8, 9, 10, 11 This may be the result of hypoxemia causing central nervous system arousal, which disrupts the rapid-eye movement and nonrapid-eye movement sleep cycle and normal sleep pattern.5

Patients with cancer may be at high risk of nocturnal hypoxemia because of pulmonary involvement, respiratory muscle weakness (e.g., caused by cachexia), and the use of opioids and other sedative drugs.12, 13, 14, 15 The primary aim of this study was to examine the prevalence of nocturnal hypoxemia in patients with cancer. A secondary aim was to begin to explore the relationships between nocturnal hypoxemia and physiological variables, opioid or other sedative drug use, daytime sleepiness, fatigue, and quality of life.

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Methods 

Subjects 

Patients with cancer admitted to two specialist palliative care units (Hayward House and Nightingale Unit) were invited to take part in the study. Those with a short prognosis (physician estimate of <4 weeks), confusion, severe hypoxia at rest (oxygen saturation [SaO2] <90%), on continuous oxygen therapy, a current chest infection or known to have obstructive sleep apnea were excluded. Those with coexistent lung disease, for example, asthma or chronic obstructive pulmonary disease, were included if it was considered stable. Patients gave written informed consent and the study was approved by the Nottingham City Hospital and Derby Royal Infirmary Ethics Committees.

Measurements 

Demographic and Other Details. Age, sex, diagnosis, presence of lung disease (primary or secondary lung cancer or noncancer lung disease), Eastern Cooperative Oncology Group (ECOG) performance status,16 body mass index (BMI), use of opioid and other sedative drugs, and recent hemoglobin were noted.

Physiological Measurements. Forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) were measured using a handheld spirometer (Micro Spirometer, Micro Medical Ltd, Rochester, Kent, UK) as the best of three recordings, with the subject standing whenever possible.

Sniff nasal inspiratory pressure (SNIP) was measured with the subject at functional residual capacity, standing whenever possible. The measurement consisted of the best of 10 maximal sniffs with one nostril occluded by a nasal pillow fixed on the top of a syringe barrel connected via a line to a pressure transducer (Pmax monitor, Rainham, Kent UK). Percent predicted values were calculated using published equations.13, 17, 18

An oximeter worn on the wrist with a finger clip probe (Minolta Pulsox 3i, USA) was used to record daytime SaO2 after 20minutes sitting resting and nocturnal SaO2 over a single night. A cotton “finger sock” was used to reduce light interference and keep the probe in place. Data from the oximeter were downloaded onto an IBM compatible personal computer and analyzed using software supplied by Minolta. Patients were considered awake when movement artifact was present and these periods were removed. At least five hours of sleep data were required for analysis.

Questionnaires. Patients completed the Epworth Sleepiness Scale (ESS), Multidimensional Fatigue Inventory (MFI), and Short Form-36 (SF-36) health questionnaires. The ESS contains eight items that ask for self-reported probability of dozing in various situations, ranging from never (0) to high probability (3). A total score of ≥11 indicates an abnormal level of daytime sleepiness, with scores of 11–14, 15–18, and >18 representing mild, moderate, and severe daytime sleepiness, respectively. Healthy volunteers and patients with a range of sleep disorders (e.g., obstructive sleep apnea, narcolepsy, and idiopathic hypersomnia) were involved in its development.19 The MFI contains 20 items answered on a five-point scale, rated 1–5, with a higher score indicating greater levels of impairment. The items are divided equally into five subscales: general fatigue, physical fatigue, reduced activity, reduced motivation, and mental fatigue, each with a possible score of 4–20.20 The SF-36 contains 36 items divided into eight domains: physical functioning, role limitations attributed to physical problems, role limitations attributed to emotional problems, social functioning, mental health, energy, bodily pain, and general health perceptions, together with a single item relating to perceived change in health over the past year. The format of the questions varies between domains. Responses are summed and transformed into a score that ranges from 0 (poor health) to 100 (good health).21

Analysis 

There is no standard definition of nocturnal hypoxemia.22 We used the definition of an overnight SaO2 of <90% for ≥2% of sleep time because this was associated with an impaired quality of life in a previous study.11 A sample size calculation was based on our primary aim; by assuming a prevalence of nocturnal hypoxemia of 10% in patients with cancer, we calculated that a sample size of 100 patients would provide an estimate of prevalence with 95% confidence intervals of ±6%.

Patients were categorized as having nocturnal hypoxemia or not, and differences were examined in age, BMI, spirometry, SNIP, hemoglobin, and ESS using a Student's t-test; in ECOG performance status, MFI, and SF-36 domains using the Mann–Whitney U test; and in sex, lung disease and use of opioid or sedative drugs by Chi-squared test. A P-value ≤0.05 was regarded as statistically significant.

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Results 

One hundred patients, 61 male, with a mean (SD) age of 70 (11) years and median (range) ECOG performance status of 3 (0–4) were recruited. Patients had cancers of the genitourinary tract (32); lung or pleura (28); colon or rectum (14); upper gastrointestinal tract (11); breast (9); and one each of squamous cell carcinoma of the skin, melanoma, carcinoid, myeloma, non-Hodgkin's lymphoma, and unknown primary. None were receiving chemo- or radiotherapy. The study group represented approximately one in eight of all admissions and had a median (range) survival of 8 (1–120) weeks (n=98).

The majority of assessments were completed in all patients except hemoglobin (99), spirometry (98), BMI (96), SNIP (94), and ECOG performance status (93). Mean (SD) duration of data analyzed was seven (1.9) hours. The mean (SD) overnight SaO2 was 94% (2%) with a range of 86%–97.5% (Fig. 1). The distribution of the percent of nighttime spent with an SaO2<90% is shown in Fig. 2. Thirty-five patients had nocturnal hypoxemia.

Demographic and Other Differences 

Patients with nocturnal hypoxemia were more likely to have lung disease (P=0.03). This consisted of primary lung cancer (9), secondary lung cancer (3), mesothelioma (3), or other lung disease (4; asthma, fibrotic lung disease, and two with previous pulmonary embolism). There were no differences in age, sex, ECOG performance status, BMI, and opioid or other sedative drug use between patients with and without nocturnal hypoxemia (Table 1).

Table 1. Demographic and Other Data
Total GroupNo HypoxemiaNocturnal HypoxemiaaP valueb
Number1006535
Age (years)70 (11)70 (12)70 (10)ns
Sex (M:F)61:3938:2723:12ns

Lung diseasec
Present412219<0.05
Absent594316

Performance statusd3 (0–4)3 (0–4)3 (0–4)ns
BMI (kg/m2)24 (5)23 (5)24 (6)ns

Drug use
Opioid or other sedative482721ns
Opioid and other sedative392910
No opioid or sedative1394

Hemoglobin (g/dL)11.1 (1.9)11.3 (2)10.6 (1.6)ns
FEV1 (% predicted)59 (21)63 (22)52 (19)0.01
FVC (% predicted)59 (18)61 (17)55 (20)ns
FEV1/FVC (%)101 (21)103 (19)96 (24)ns
SNIP (% predicted)36 (23)38 (26)34 (19)ns
Daytime SaO295 (2)96 (2)94 (3)0.01

Mean (SD) values unless specified otherwise.

ns=not significant.

aOvernight SaO2 of <90% for ≥2% of sleep time.

bDifference between no hypoxemia and nocturnal hypoxemia groups.

cPrimary or secondary lung cancer or noncancer disease.

dMedian (range).

Physiological Differences 

Patients with nocturnal hypoxemia had lower FEV1 % predicted and daytime SaO2 compared to those without hypoxemia, but the absolute differences were small, with mean (95% CI) differences of 11% (3–20) and 1% (0.3–2), respectively (Table 1). There were no significant differences in hemoglobin, FVC, FEV1/FVC, and SNIP. The values of FEV1/FVC and SNIP were in keeping with a restrictive defect and inspiratory muscle weakness (Table 1).

Differences in Daytime Sleepiness, Fatigue, and Quality of Life 

Mean ESS score was ≥11 in patients with and without nocturnal hypoxemia, indicating an abnormal level of daytime sleepiness. ESS scores were higher in patients with hypoxemia but the difference was not significant (Table 2). Patients with nocturnal hypoxemia had greater levels of mental fatigue (MFI) and emotional role limitation (SF-36) but a lower perceived change in health over the past year (SF-36), with mean (95% CI) differences of 2 (0.3–5), 19 (1–36), and 9 (1–17), respectively (Table 2). However, these domains of the SF-36, together with the physical role limitation domain, contain median values of zero, suggesting a lack of sufficient sensitivity for the lower levels of ill health seen in this group of patients.

Table 2. Daytime Sleepiness, Fatigue, and Quality of Life
ScaleNo HypoxemiaNocturnal HypoxemiaaP value
Epworth sleepiness scaleb11 (5)13 (5)Ns

Multidimensional fatigue inventoryc
General fatigue16 (14–19)16 (14–16)ns
Physical fatigue18 (16–20)18 (16–20)ns
Reduced activity19 (16–20)17 (15–20)ns
Reduced motivation11.5 (6–16)13 (7.7–16)ns
Mental fatigue9.5 (5–14)13 (9–17)0.02

Short Form-36 health questionnairec
Physical function2.5 (0–10)5 (0–15)ns
Role limitation: physical0 (0–0)0 (0–0)ns
Role limitation: emotional0 (0–0)0 (0–100)0.04
Social functioning11 (0–41)22 (8–59)ns
Mental health60 (49–72)70 (41–87)ns
Energy20 (9–35)28 (10–45)ns
Pain11 (0–44)33 (11–47)ns
General health perception15 (5–32)20 (5–36)ns
Change in health0 (0–25)25 (0–25)0.02

ns=not significant.

aOvernight SaO2 of <90% for ≥2% of sleep time.

bMean (SD).

cMedian (25–75th centile).

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Discussion 

This is the first study to explore nocturnal hypoxemia in patients with cancer admitted to a specialist palliative care unit. They represent a group of patients who would generally survive long enough to potentially benefit from an intervention, for example, supplemental oxygen.

Using the definition of nocturnal hypoxemia as an overnight SaO2 of <90% for ≥2% of sleep time,11 about one-third of patients had nocturnal hypoxemia and these had greater levels of mental fatigue (difficulty concentrating) compared to patients without nocturnal hypoxemia. However, there was no significant difference in the level of daytime sleepiness, with abnormally high levels seen in both groups. The most plausible explanation is that nocturnal hypoxemia is only one of several causes of daytime sleepiness that coexist in patients with cancer. There may be other causes of sleep disturbance, such as increased cytokine production, unrelieved pain, and mood disturbance.23 It also could reflect the relatively small proportion of sleep time, ≥2%, used in our definition of nocturnal hypoxemia compared to those used by other groups, for example, >10% or ≥30% of sleep time.24, 25 This also may explain why there were few other differences between the two groups, apart from patients with nocturnal hypoxia being more likely to have lung disease, and a lower FEV1 and daytime SaO2. Even so, none of these associations appeared strong enough to be of use in predicting the presence of nocturnal hypoxemia.

The high FEV1/FVC ratio and low SNIP values suggest a restrictive ventilatory defect due to inspiratory muscle weakness. Despite the reasonable mean BMI values, this is most likely a result of the cachexia syndrome. Future studies should consider also collecting data on percentage weight loss to help examine this further.

Pulse oximetry was used for this study because it is simple, cheap, and more accessible than a formal sleep study. A single night of oximetry is considered a useful screening tool for the obstructive sleep apnea/hypopnea syndrome.26 However, there are limitations to the use of oximetry alone for diagnostic purposes. For example, the classic sawtooth pattern seen in obstructive sleep syndromes can also occur in periodic/Cheyne-Stokes breathing.26 Further, although we assumed that patients were asleep during the periods free from movement artifact, this can only be accurately determined using a more detailed sleep study. Thus, future studies should consider the use of more detailed sleep studies to confirm the presence, cause, and impact of nocturnal hypoxemia in this group of patients.

The SF-36 has been used in other studies of nocturnal hypoxemia and also in patients with cancer and was included mainly for comparative purposes.11, 27 However, in our group of patients, apart from mental health, scores were low, and three of the eight domains contained median values of zero. Such a floor effect is a recognized problem with severely ill populations and to overcome this, it is recommended to supplement the SF-36 with additional items that represent the extreme low end of the continuum.28 Alternatively, the use of assessments that are specifically aimed at this population should be considered for future studies (e.g., EORTC QLQ-C15-PAL).29

Finally, we found no relationship between opioid and other sedative drug use and nocturnal hypoxemia. However, others have found abnormal breathing patterns in patients on long-term opioid therapy and more detailed sleep studies would be required to exclude any effect with certainty.14

In summary, nocturnal hypoxemia is common in this group of patients with advanced cancer and may contribute to difficulty in concentrating. Future studies should consider the use of more detailed sleep studies to examine this finding more closely. Although the ESS and the MFI appeared applicable to this group, the SF-36 functioned less well and we recommend the use of a supplementary (more specific) quality-of-life scale.

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Acknowledgments 

The authors would like to thank the patients and staff who took part or supported this study, and Sarah Lewis for statistical advice.

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References 

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 This project received funding from the Association for Palliative Medicine of Great Britain and Ireland/Napp Research Bursary, Hayward House Cancer Care Trust, Next, Peel Medical Research Trust, and the Royal Society of Medicine.

PII: S0885-3924(08)00203-0

doi:10.1016/j.jpainsymman.2007.11.007

Journal of Pain and Symptom Management
Volume 36, Issue 4 , Pages 351-357, October 2008

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