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Recombinant Zoster Vaccine (Shingrix): Real-World Effectiveness in the First 2 Years Post-Licensure

Author/s: 
Izurieta, H. S., Wu, X., Forshee, R., Lu, Y., Sung, H. M., Agger, P. E., Chillarige, Y., Link-Gelles, R., Lufkin, B., Wernecke, M., MaCurdy, T. E., Kelman, J., Dooling, K.

Background
Shingrix (recombinant zoster vaccine) was licensed to prevent herpes zoster, dispensed as 2 doses given 2–6 months apart among adults aged ≥50 years. Clinical trials yielded efficacy of >90% for confirmed herpes zoster, but post-market performance has not been evaluated. Efficacy of a single dose and a delayed second dose and efficacy among persons with autoimmune or immunosuppressive conditions have not been studied. We aimed to assess post-market vaccine effectiveness of Shingrix.

Methods
We conducted a cohort study among Medicare Part D community-dwelling beneficiaries aged >65 years. Herpes zoster was identified using a medical office visit diagnosis with treatment, and postherpetic neuralgia was identified using a validated algorithm. We used inverse probability of treatment weighting to improve cohort balance and marginal structural models to estimate hazard ratios.

Results
We found a vaccine effectiveness of 70.1% (95% confidence interval [CI], 68.6–71.5) and 56.9% (95% CI, 55.0–58.8) for 2 and 1 doses, respectively. The 2-dose vaccine effectiveness was not significantly lower for beneficiaries aged >80 years, for second doses received at ≥180 days, or for individuals with autoimmune conditions. The vaccine was also effective among individuals with immunosuppressive conditions. Two-dose vaccine effectiveness against postherpetic neuralgia was 76.0% (95% CI, 68.4–81.8).

Conclusions
This large real-world observational study of the effectiveness of Shingrix demonstrates the benefit of completing the 2-dose regimen. Second doses administered beyond the recommended 6 months did not impair effectiveness. Our effectiveness estimates were lower than the clinical trials estimates, likely due to differences in outcome specificity.

Diagnostic Accuracy of Symptoms, Physical Signs, and Laboratory Tests for Giant Cell Arteritis: A Systematic Review and Meta-analysis

Author/s: 
van der Geest, Kornelis S. M., Sandovici , S., Brouwer, Elisabeth, Mackie, S.L.

Abstract

Importance: Current clinical guidelines recommend selecting diagnostic tests for giant cell arteritis (GCA) based on pretest probability that the disease is present, but how pretest probability should be estimated remains unclear.

Objective: To evaluate the diagnostic accuracy of symptoms, physical signs, and laboratory tests for suspected GCA.

Data sources: PubMed, EMBASE, and the Cochrane Database of Systematic Reviews were searched from November 1940 through April 5, 2020.

Study selection: Trials and observational studies describing patients with suspected GCA, using an appropriate reference standard for GCA (temporal artery biopsy, imaging test, or clinical diagnosis), and with available data for at least 1 symptom, physical sign, or laboratory test.

Data extraction and synthesis: Screening, full text review, quality assessment, and data extraction by 2 investigators. Diagnostic test meta-analysis used a bivariate model.

Main outcome(s) and measures: Diagnostic accuracy parameters, including positive and negative likelihood ratios (LRs).

Results: In 68 unique studies (14 037 unique patients with suspected GCA; of 7798 patients with sex reported, 5193 were women [66.6%]), findings associated with a diagnosis of GCA included limb claudication (positive LR, 6.01; 95% CI, 1.38-26.16), jaw claudication (positive LR, 4.90; 95% CI, 3.74-6.41), temporal artery thickening (positive LR, 4.70; 95% CI, 2.65-8.33), temporal artery loss of pulse (positive LR, 3.25; 95% CI, 2.49-4.23), platelet count of greater than 400 × 103/μL (positive LR, 3.75; 95% CI, 2.12-6.64), temporal tenderness (positive LR, 3.14; 95% CI, 1.14-8.65), and erythrocyte sedimentation rate greater than 100 mm/h (positive LR, 3.11; 95% CI, 1.43-6.78). Findings that were associated with absence of GCA included the absence of erythrocyte sedimentation rate of greater than 40 mm/h (negative LR, 0.18; 95% CI, 0.08-0.44), absence of C-reactive protein level of 2.5 mg/dL or more (negative LR, 0.38; 95% CI, 0.25-0.59), and absence of age over 70 years (negative LR, 0.48; 95% CI, 0.27-0.86).

Conclusions and relevance: This study identifies the clinical and laboratory features that are most informative for a diagnosis of GCA, although no single feature was strong enough to confirm or refute the diagnosis if taken alone. Combinations of these symptoms might help direct further investigation, such as vascular imaging, temporal artery biopsy, or seeking evaluation for alternative diagnoses.

Diagnosis of Pulmonary Embolism with d-Dimer Adjusted to Clinical Probability

Author/s: 
Kearon, C, de Wit, K, Parpia, S, Schulman, S, Afilalo, M, Hirsch, A, Spencer, FA, Sharma, S, D'Aragon, F, Deshaies, JF, Le Gal, G, Lazo-Langer, A, Wu, C, Rudd-Scott, L, Bates, SM, Julian, JA, PEGeD Study Investigators

BACKGROUND:

Retrospective analyses suggest that pulmonary embolism is ruled out by a d-dimer level of less than 1000 ng per milliliter in patients with a low clinical pretest probability (C-PTP) and by a d-dimer level of less than 500 ng per milliliter in patients with a moderate C-PTP.

METHODS:

We performed a prospective study in which pulmonary embolism was considered to be ruled out without further testing in outpatients with a low C-PTP and a d-dimer level of less than 1000 ng per milliliter or with a moderate C-PTP and a d-dimer level of less than 500 ng per milliliter. All other patients underwent chest imaging (usually computed tomographic pulmonary angiography). If pulmonary embolism was not diagnosed, patients did not receive anticoagulant therapy. All patients were followed for 3 months to detect venous thromboembolism.

RESULTS:

A total of 2017 patients were enrolled and evaluated, of whom 7.4% had pulmonary embolism on initial diagnostic testing. Of the 1325 patients who had a low C-PTP (1285 patients) or moderate C-PTP (40 patients) and a negative d-dimer test (i.e., <1000 or <500 ng per milliliter, respectively), none had venous thromboembolism during follow-up (95% confidence interval [CI], 0.00 to 0.29%). These included 315 patients who had a low C-PTP and a d-dimer level of 500 to 999 ng per milliliter (95% CI, 0.00 to 1.20%). Of all 1863 patients who did not receive a diagnosis of pulmonary embolism initially and did not receive anticoagulant therapy, 1 patient (0.05%; 95% CI, 0.01 to 0.30) had venous thromboembolism. Our diagnostic strategy resulted in the use of chest imaging in 34.3% of patients, whereas a strategy in which pulmonary embolism is considered to be ruled out with a low C-PTP and a d-dimer level of less than 500 ng per milliliter would result in the use of chest imaging in 51.9% (difference, -17.6 percentage points; 95% CI, -19.2 to -15.9).

CONCLUSIONS:

A combination of a low C-PTP and a d-dimer level of less than 1000 ng per milliliter identified a group of patients at low risk for pulmonary embolism during follow-up. (Funded by the Canadian Institutes of Health Research and others; PEGeD ClinicalTrials.gov number, NCT02483442.).

Keywords 
pulmonary embolism PE d-dimer CT computed tomography

Mobile phone text messaging and app-based interventions for smoking cessation

Author/s: 
Whittaker, R, McRobbie, H, Bullen, C, Rodgers, A, Gu, Y, Dobson, R

Abstract

Background

Mobile phone‐based smoking cessation support (mCessation) offers the opportunity to provide behavioural support to those who cannot or do not want face‐to‐face support. In addition, mCessation can be automated and therefore provided affordably even in resource‐poor settings. This is an update of a Cochrane Review first published in 2006, and previously updated in 2009 and 2012.

Objectives

To determine whether mobile phone‐based smoking cessation interventions increase smoking cessation rates in people who smoke.

Search methods

For this update, we searched the Cochrane Tobacco Addiction Group's Specialised Register, along with clinicaltrials.gov and the ICTRP. The date of the most recent searches was 29 October 2018.

Selection criteria

Participants were smokers of any age. Eligible interventions were those testing any type of predominantly mobile phone‐based programme (such as text messages (or smartphone app) for smoking cessation. We included randomised controlled trials with smoking cessation outcomes reported at at least six‐month follow‐up.

Data collection and analysis

We used standard methodological procedures described in the Cochrane Handbook for Systematic Reviews of Interventions. We performed both study eligibility checks and data extraction in duplicate. We performed meta‐analyses of the most stringent measures of abstinence at six months' follow‐up or longer, using a Mantel‐Haenszel random‐effects method, pooling studies with similar interventions and similar comparators to calculate risk ratios (RR) and their corresponding 95% confidence intervals (CI). We conducted analyses including all randomised (with dropouts counted as still smoking) and complete cases only.

Main results

This review includes 26 studies (33,849 participants). Overall, we judged 13 studies to be at low risk of bias, three at high risk, and the remainder at unclear risk. Settings and recruitment procedures varied across studies, but most studies were conducted in high‐income countries. There was moderate‐certainty evidence, limited by inconsistency, that automated text messaging interventions were more effective than minimal smoking cessation support (RR 1.54, 95% CI 1.19 to 2.00; I2 = 71%; 13 studies, 14,133 participants). There was also moderate‐certainty evidence, limited by imprecision, that text messaging added to other smoking cessation interventions was more effective than the other smoking cessation interventions alone (RR 1.59, 95% CI 1.09 to 2.33; I2 = 0%, 4 studies, 997 participants). Two studies comparing text messaging with other smoking cessation interventions, and three studies comparing high‐ and low‐intensity messaging, did not show significant differences between groups (RR 0.92 95% CI 0.61 to 1.40; I2 = 27%; 2 studies, 2238 participants; and RR 1.00, 95% CI 0.95 to 1.06; I2 = 0%, 3 studies, 12,985 participants, respectively) but confidence intervals were wide in the former comparison. Five studies compared a smoking cessation smartphone app with lower‐intensity smoking cessation support (either a lower‐intensity app or non‐app minimal support). We pooled the evidence and deemed it to be of very low certainty due to inconsistency and serious imprecision. It provided no evidence that smartphone apps improved the likelihood of smoking cessation (RR 1.00, 95% CI 0.66 to 1.52; I2 = 59%; 5 studies, 3079 participants). Other smartphone apps tested differed from the apps included in the analysis, as two used contingency management and one combined text messaging with an app, and so we did not pool them. Using complete case data as opposed to using data from all participants randomised did not substantially alter the findings.

Authors' conclusions

There is moderate‐certainty evidence that automated text message‐based smoking cessation interventions result in greater quit rates than minimal smoking cessation support. There is moderate‐certainty evidence of the benefit of text messaging interventions in addition to other smoking cessation support in comparison with that smoking cessation support alone. The evidence comparing smartphone apps with less intensive support was of very low certainty, and more randomised controlled trials are needed to test these interventions.

Plain Language Summary

Can programmes delivered by mobile phones help people to stop smoking?

Background

Tobacco smoking is a leading cause of preventable death. Mobile phones can be used to support people who want to quit smoking. In this review, we have focused on programmes that use text messages or smartphone apps to do so.

Search date

We searched for published and unpublished studies in October 2018.

Study characteristics

We included 26 randomised controlled studies (involving over 33,000 people) that compared smoking quit rates in people who received text messages or smartphone apps to help them quit, with people who did not receive these programmes. We were interested in studies that measured smoking for six months or longer.

Key results

We found that text messaging programmes may be effective in supporting people to quit, increasing quit rates by 50% to 60%. This was the case when they were compared to minimal support or were tested as an addition to other forms of stop‐smoking support. There was not enough evidence to determine the effect of smartphone apps.

Quality and completeness of the evidence

Most of the studies were of high quality, although three studies had high drop out rates. We are moderately confident in the results of the text messaging interventions, but there were some issues with unexplained differences between study findings and for some comparisons there was not much data. We have low confidence in the results concerning smartphone apps, and more studies are needed in this field.

Keywords 
smoking cessation mobile phone tobacco tobacco use text message
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