Psychosocial Risk Factors for Lung Cancer

Abstract

The existence of psychosocial risk factors for the development of malignancy has been postulated by many investigators. This study investigated selected psychosocial factors as predictors of malignancy. 110 male patients with undiagnosed subacute or chronic pulmonary x-ray lesions participated in a semistructured interview. Ratings were made of 5 subscales: 1) childhood instability, 2) job stability, 3) marriage stability, 4) lack of plans for the future, and 5) recent significant loss. The composite scale correctly predicted the diagnosis of 53 (80%) of the 66 patients with benign disease and 27 (61 %) of the 44 with lung cancer. The scale was at least as important as smoking history in predicting diagnoses. Thus, significant psychosocial risk factors for the development of malignant disease might well be incorporated in selecting highrisk individuals for cytological or other screening for lung cancer.

Possible links between behavioral and physiological indices of tiredness, fatigue, and exhaustion in advanced cancer

“…The limiting levels of skeletal muscle by these criteria are <7.26 kg/m 2 for men and <5.45 kg/m 2 in women [6,7,31]. We think that the muscle wasting that occurs with age, when coupled with the muscle wasting that occurs in the context of advanced cancer, may be sufficient to trigger tiredness, fatigue, or exhaustion despite normal hemoglobin levels.…”

Incarceration as Exposure: The Prison, Infectious Disease, and Other Stress-Related Illnesses

“…More specifically, odds ratios (the exponentiation of the logistic regression estimates) indicate that incarcerated individuals are at least four times as likely to report a diagnosis of hypertension (Yan et al 2003), emotional and psychological problems (Pearlin 1999), or chronic lung illness (Horne and Picard 1979;Holt 1993;Cohen, Doyle, and Skoner 1999). Finally, exinmates are almost twice as likely to be diagnosed with heart problems (Greenberg 1993).…”

Stress and Health

“…The design of studying an undifferentiated group of patients awaiting biopsy results, and trying to predict for whom the later biopsy will reveal malignancy, has been used by some investigators as a compromise between a prospective and a retrospective design that may eliminate some of the bias due to the impact of the disease itself (e. g. 62,76,189). The results are not easy to interpret and the predictors do not fit a compelling cluster; this may be because data analysis involves often a purely statistical search among a large set of predictors.…”