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Iodine chemistry has noteworthy impacts on the oxidising capacity of the marine boundary layer (MBL) through the depletion of ozone (O3) and changes to HOx (OH=HO2) and NOx (NO=NO2) ratios. Hitherto, studies have shown that the reaction of atmospheric O3 with surface seawater iodide (I-) contributes to the flux of iodine species into the MBL mainly as hypoiodous acid (HOI) and molecular iodine (I2). Here, we present the first concomitant observations of iodine oxide (IO), O3 in the gas phase, and sea surface iodide concentrations. The results from three field campaigns in the Indian Ocean and the Southern Ocean during 2015 2017 are used to compute reactive iodine fluxes in the MBL. Observations of atmospheric IO by multi-axis differential optical absorption spectroscopy (MAX-DOAS) show active iodine chemistry in this environment, with IO values up to 1 pptv (parts per trillion by volume) below latitudes of 40° S. In order to compute the sea-to-air iodine flux supporting this chemistry, we compare previously established global sea surface iodide parameterisations with new regionspecific parameterisations based on the new iodide observations. This study shows that regional changes in salinity and sea surface temperature play a role in surface seawater iodide estimation. Sea air fluxes of HOI and I2, calculated from the atmospheric ozone and seawater iodide concentrations (observed and predicted), failed to adequately explain the detected IO in this region. This discrepancy highlights the need to measure direct fluxes of inorganic and organic iodine species in the marine environment. Amongst other potential drivers of reactive iodine chemistry investigated, chlorophyll a showed a significant correlation with atmospheric IO (R D 0:7 above the 99 % significance level) to the north of the polar front. This correlation might be indicative of a biogenic control on iodine sources in this region.

Although multidimensional instruments are usually used to measure quality of life in advanced cancer patients, recent research suggests that single-item assessments can provide a reliable measure. Using the Functional Assessment of Cancer Therapy-General (FACT-G) instrument as a gold standard, we assessed the performance of the Edmonton Symptom Assessment System "feeling of well-being" (ESAS WB) item. We reviewed the data from 213 patients enrolled in six clinical trials. We determined the association between baseline ESAS WB and FACT-G total and subscale domain scores (Physical Well-being [PWB], Social/Family Well-being [SWB], Emotional Well-being [EWB], and Functional Well-being [FWB]. We also calculated the association between baseline (T1) and second (T2) observations of ESAS WB and of FACT-G total score. In addition, we predicted the change in FACT-G predicted by the ESAS WB score using regression analysis. Mean age was 60 (SD 12) years and 48% were female. The Spearman correlation coefficient of ESAS WB and FACT-G was -0.48 (P < 0.0001). Correlations with FACT-G subscale domains were also highly significant, except for the SWB domain (P = 0.08). The Pearson correlation coefficient for T1-T2 in ESAS WB and FACT-G for 146 patients was -0.36 (P < 0.0001). The change in ESAS WB corresponding to FACT-G published minimally important difference was -0.24 for 3, -1.55 for 5, and -2.87 for 7, respectively. These results suggest that the single-item measure ESAS WB best reflects the total score on the FACT-G and PWB, EWB, and FWB domains but not on the SWB domain. © 2010 U.S. Cancer Pain Relief Committee.

Although multidimensional instruments are usually used to measure quality of life in advanced cancer patients, recent research suggests that single-item assessments can provide a reliable measure. Using the Functional Assessment of Cancer Therapy-General (FACT-G) instrument as a gold standard, we assessed the performance of the Edmonton Symptom Assessment System "feeling of well-being" (ESAS WB) item. We reviewed the data from 213 patients enrolled in six clinical trials. We determined the association between baseline ESAS WB and FACT-G total and subscale domain scores (Physical Well-being [PWB], Social/Family Well-being [SWB], Emotional Well-being [EWB], and Functional Well-being [FWB]. We also calculated the association between baseline (T1) and second (T2) observations of ESAS WB and of FACT-G total score. In addition, we predicted the change in FACT-G predicted by the ESAS WB score using regression analysis. Mean age was 60 (SD 12) years and 48% were female. The Spearman correlation coefficient of ESAS WB and FACT-G was -0.48 (P < 0.0001). Correlations with FACT-G subscale domains were also highly significant, except for the SWB domain (P = 0.08). The Pearson correlation coefficient for T1-T2 in ESAS WB and FACT-G for 146 patients was -0.36 (P < 0.0001). The change in ESAS WB corresponding to FACT-G published minimally important difference was -0.24 for 3, -1.55 for 5, and -2.87 for 7, respectively. These results suggest that the single-item measure ESAS WB best reflects the total score on the FACT-G and PWB, EWB, and FWB domains but not on the SWB domain. © 2010 U.S. Cancer Pain Relief Committee.

Objectives: The improvement of quality of life (QOL) is a cornerstone of good palliative care. QOL is a subjective and complex multi-dimensional concept, so it is usually measured using multi-dimensional instruments. Recently, authors have suggested that brief single-item global assessments can provide a reliable measure of overall QOL. Using the Functional Assessment of Cancer Therapy - General (FACT-G) instrument as a gold standard, we assessed the performance of the Edmonton Symptom Assessment System 'feeling of well-being' item (ESAS WB). Method(s): After obtaining IRB approval, we retrospectively reviewed the data from six prospective clinical trials conducted by our group in advanced cancer patients. We determined the levels of association between baseline ESAS WB and FACT-G total and subscale domain scores (Physical (Pwb), Social/Family (Swb), Emotional (Ewb), and Functional (Fwb) Well-Being) and also between the nine ESAS symptom intensity scores using Spearman correlation coefficients. We also calculated the change between the baseline (T1) and second (T2) observations of ESAS WB and of FACT-G total score and determined their level of association using a Pearson correlation coefficient. We also predicted the change in FACT-G as predicted by the ESAS WB score using regression analysis. Result(s): Mean age of the 218 trial participants was 60 (SD 12) years and 48% were female. Spearman correlations between ESAS WB and FACT-G and ESAS scores are shown in the table. The Pearson correlation coefficient for T1 - T2 in ESAS WB and FACT-G for 146 patients was - 0.36 (p<0.0001). The regression analysis was highly significant (p<0.0001). The change in ESAS WB corresponding to FACT-G published minimally important difference (MID) was -0.24 for 3, -1.55 for 5, and -2.87 for 7, respectively. Conclusion(s): ESAS WB is a practical instrument for the clinical setting but appears to correlate less well with the Swb domain of FACT-G.

Objectives: The improvement of quality of life (QOL) is a cornerstone of good palliative care. QOL is a subjective and complex multi-dimensional concept, so it is usually measured using multi-dimensional instruments. Recently, authors have suggested that brief single-item global assessments can provide a reliable measure of overall QOL. Using the Functional Assessment of Cancer Therapy - General (FACT-G) instrument as a gold standard, we assessed the performance of the Edmonton Symptom Assessment System 'feeling of well-being' item (ESAS WB). Method(s): After obtaining IRB approval, we retrospectively reviewed the data from six prospective clinical trials conducted by our group in advanced cancer patients. We determined the levels of association between baseline ESAS WB and FACT-G total and subscale domain scores (Physical (Pwb), Social/Family (Swb), Emotional (Ewb), and Functional (Fwb) Well-Being) and also between the nine ESAS symptom intensity scores using Spearman correlation coefficients. We also calculated the change between the baseline (T1) and second (T2) observations of ESAS WB and of FACT-G total score and determined their level of association using a Pearson correlation coefficient. We also predicted the change in FACT-G as predicted by the ESAS WB score using regression analysis. Result(s): Mean age of the 218 trial participants was 60 (SD 12) years and 48% were female. Spearman correlations between ESAS WB and FACT-G and ESAS scores are shown in the table. The Pearson correlation coefficient for T1 - T2 in ESAS WB and FACT-G for 146 patients was - 0.36 (p<0.0001). The regression analysis was highly significant (p<0.0001). The change in ESAS WB corresponding to FACT-G published minimally important difference (MID) was -0.24 for 3, -1.55 for 5, and -2.87 for 7, respectively. Conclusion(s): ESAS WB is a practical instrument for the clinical setting but appears to correlate less well with the Swb domain of FACT-G.